Luminaries

Professor Patricia Davidson: Good afternoon everyone, I'm Patricia Davidson, Vice-Chancellor of the University of Wollongong. Just while we're waiting for everyone to join us, maybe you'd like to share in the chat where you're joining us from today, and any wishes that you would like to send Justin.  

So colleagues we might get started, people are slowly joining us. As I mentioned, I'm Patricia Davidson, I have the honour and privilege of being the Vice-Chancellor of the University of Wollongong in Australia, and it's wonderful to see colleagues from around the globe here today to celebrate Justin's exceptional achievements. It's such a pleasure to welcome each and every one of you here today.  

Today we're here to acknowledge Professor Justin Yerbury, a celebrated molecular biologist, a friend and colleague to many who is making significant contributions to better understand motor neuron disease. Since before we start today, I would like to acknowledge Country, and I know that people are joining us from places all around the world.  

And on behalf of the University of Wollongong, I would like to acknowledge that Country for Aboriginal peoples is an interconnected set of ancient and sophisticated relationships. The University of Wollongong spreads across many interrelated Aboriginal countries that are bound by this sacred landscape, an intimate relationship with that landscape since creation from Sydney to the Southern Highlands to the south coast. From freshwater to bitter water to salt, from city to urban to rural.  

The University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space that has kept alive the relationship between all living things. The University of Wollongong acknowledges the devastating impact of colonisation on our campuses footprint and commit ourselves to truth telling, healing and education. And we also acknowledge First Nations people from all around the world.  

We're so delighted today to be able to have this event to honour the work of Justin Yerbury and his colleagues. Justin was inspired to join the research effort to address motor neuron disease after discovering a family history of the condition and was already leading a research team when he himself was diagnosed in 2016. And in spite of his own challenges and battles with this condition, he continues to lead his team at the University of Wollongong towards finding a cure.  

And beyond the four walls of the University of Wollongong, as we can see from people here today, he's motivated and inspired a generation of new scholars and scientists and spurred many all around the world to address this challenging condition.  

Today is an opportunity for us to be together with Justin's family, friends and peers. And to acknowledge and celebrate his significant achievements and contributions to the University of Wollongong and to science. His achievements have been widely recognised. 

In 2020, Justin received an Order of Australia Award and in 2022 was awarded the keys to the City of Wollongong and the prestigious University of New South Wales Eureka Prize for Scientific Research.  

Justin joins us today together with his wife, Rachel, their daughters Tahlia and Maddy, and Justin's father, Fred. A very warm welcome to you today. And thank you for sharing Justin with us.  

I encourage members of the audience to submit their own questions using the Q&A function, and we'll try to get through as many questions as possible. And now it's my great pleasure to introduce you to Dr. Luke McAlary, who will introduce you to the your great lab team here at the University of Wollongong. Welcome, Luke.  

Dr Luke McAlary: Thanks, Patricia, for that kind introduction for Justin and the group. And hello to everyone who's joined us today. So I am going to share my slides. So I've been given the sort of privilege to introduce Justin and who he is. And Patricia's touched on some of the things already that make Justin who he is. And this is sort of a bunch of slides about what I think makes Justin Justin, and such an amazing academic, which is why we're here to celebrate him.  

So, Justin is a local, which is one of the most amazing things, because often you don't realise how many people in the local area are so amazing, especially scientists and UOW has really helped us do that. But Patricia has already talked about Justin's situation in which he discovered that people in his family were succumbing to motor neuron disease. And he made the decision that very few people really do in their lifetime and that is "I'm going to solve this almost unassailable problem myself". And that is exactly what he's been doing over the past decades, trying to solve one of the hardest problems that anyone or any really field of science could ever face.  

But I want to talk more about Justin, the academic. So what makes Justin an academic? And I split what makes someone an academic into three different things. So in particularly for Justin, so what makes him an academic is that he is a scientist, a bacon and a leader. And I'm going to talk to these three things that over the course of my presentation here. So first off, Justin, as a scientist. So in science, we've got to publish research papers, and Justin's been extremely prolific at doing this. So since he started his career in 2005, he has published over 64 academic research articles and has been cited over 5,500 times, which is no easy feat. He is in collaboration with other researchers around the world and Australia, obtained over $16.8 million in competitive funding since 2007, which again is a major achievement and not really something that a lot of people have achieved. As Trish said he was a 2022 Eureka Prize winner, which is a very prestigious Australian Science Award. He won the 2022 Premier's Prize for Medical Biological Science, another very prestigious award, and was the 2020 Order of Australia recipient, which is a huge sort of Australia-wide recognition of what Justin has done.  

So what more about Justin's science? So I'm not going to go into too much detail, but there's two major areas that I think Justin has really, really helped in the MND field and area number one is this concept of super saturation of proteins in motor neuron disease, of which Justin was the key driver in this research. And that's been a real big impact on the field and how we understand the disease as it stands. You're going to hear more about this from the Yerbury Lab research team and then also Justin's contribution to the idea of prion like propagation and MND, which is another important way of understanding how this disease occurs, which again, you'll hear from the rest of the research team. So the second thing I'd like to talk to is Justin as a beacon. So Justin's had global collaborations with leading scientists around the world involving the motor neuron disease and in general, an idea called protein homeostasis.  

And Justin himself is a key figure in the Australian MND research community, often being found, talking to pretty much anyone within that community who is serious about curing this disease. Justin knows pretty much all of them, which is excellent, and he's also a supporter of open science and shares pretty much anything that he has, whether that be ideas, reagents and knowledge. And so I want to show off just how much of a beacon he is by showing you a small snapshot of his global collaboration network. So here is researcher, Neil Cashman from Canada. Jacob Ayres from the United States, Giorgio Farran from Cambridge, UK, Justin Benesch from Oxford. Chris Dobson one of the major, probably collaborators Justin has, a dear friend of Justin's. Michaela Vendruscolo, Janet Kumita, Benedetta Sbrollini. Stephen Oliver. And yeah, so you can see there's a big concentration around Cambridge, and that's because Justin spent some years there studying with Chris Dobson, who is one of Justin's close friends.  

And so I'd like to narrow down now on Australia, because there's a few of these people here and it's quite a big network in Australia. So you've got all these people from all across Australia who have collaborated, worked with Justin, many of them quite closely and have really contributed to Justin's science and he has contributed to their science as well because we don't do research in a vacuum. Often it's a team effort and this is a team of people that Justin is able to create.  

And so speaking of teams, the local UOW team is especially important because there wasn't any MND research going on in at this university until Justin started. And he managed to get local experts such as Heath Ecroyd, Lezanne Ooi, Mark Wilson, Kara Perrow and Ron Sluyter, some of whom you'll hear from later in the session today to really start engaging in this research here. And Justin was a big part of that.  

And so the final thing I want to touch on for who Justin Yerbury is as an academic is a leader. So he's been leading a research team since 2007, and he's had 21 students graduate, ten of those PhDs, 11 of them honours, which is, again, a hard thing to do to mentor someone through such a trying time in their life. And he also has the best looking team at UOW, I believe. And so just to show you how good looking they are, I've made this slide here. And this slide is sort of like it's a montage which for quite a while. But these are the people, past and present who have worked closely in Justin Yerbury's lab. And some of these people still work here with Justin. And some of them have gone on to great things. Some of them have gone on to become postdoctoral researchers, scientists in their own right, while some of them have gone on to work in industrial capacity or have left science altogether. 

But not a person in here said they haven't had some part of their life affected by Justin's drive, passion and love for research. And so this is really the team of people that Justin has built up over the years. And with that, I'd like to bring it back to the three major things that I think make Justin the academic, a scientist, a beacon and a leader. And I want to reiterate that again. Justin Yerbury, the scientist, the beacon, the leader and the absolute legend.  

And so with that, I will close my remarks and I'll open it to Natalie Farrawell, who has worked with Justin Yerbury for the last ten years and is sort of the center of the laboratory, really, she is an expert in her own right. So I will begin playing that.  

Natalie Farrawell: Hi, my name is Natalie Farwell and I'm a senior research assistant that has had the pleasure of working with Justin for the past ten years. Today, I'm going to give you some brief background on MND and Justin's research and highlight some of the models we use to study the disease in the lab.  

So motor neuron disease, or MND, is a fatal neurodegenerative disease characterised by the death of motor neurons or nerve cells. These nerve cells control our muscles responsible for voluntary movement, and as MND progresses and motor neuron start to die, these muscles start to waste away, leading to paralysis and eventually death by respiratory failure. The average life expectancy for someone suffering from the disease is around two and a half years. And while each day two people die from MND, another two are diagnosed with the disease.  

The cause of most cases of MND are unknown. And importantly, currently, there are no effective treatments for the disease. The pathology of MND is now marked by the deposition of large protein clumps called protein aggregates within motor neurons. Now, the proteins within these aggregates vary depending on the genetics of the disease. And here are just a few examples some of the proteins you might find within these aggregates that are associated with the disease.  

So SOD1 was the first protein identified to be associated with MND. And a lot of today's talks will focus on this protein. Now, it is not yet known whether these protein aggregates are a cause or consequence of the disease. But a major focus of Justin's research has been how these aggregates disrupt essential cellular processes, which ultimately results in the death of motor neurons.  

So let me tell you a little bit more about the process of protein aggregation. In a healthy motor neuron, we have millions of proteins moving around cells, and these proteins carry out a variety of different functions, such as moving molecules from one part of the cell to another in order to perform their function. Proteins need to be folded into the correct shape or form. If we liken these proteins in a cell to maltesers in a flask, you can see that the proteins or the maltesers in this case are able to freely move around the flask. However, under conditions of stress, such as a mutation in a gene associated with MND, these proteins become misfolded and sticky, making them prone to form these protein aggregates that we see in the motor neurons.  

If we go back to our malteaser analogy and expose our malteasers to a bit of stress, such as heat stress, you can see they become sticky and form clumps that are no longer able to move around the flask like they could before. And this is what we see happen to the proteins in motor neuron disease. There are a number of ways we can study the disease in the lab, and more often than not, our first port of call is a cell culture model. So we can culture motor neuron like cells in a dish and introduce MND associated proteins such as SOD1 which can be tagged with a fluorescent protein such as the green fluorescent protein from a jellyfish, which allows us to visualise the distribution within the cell. And we can use these models to assess the effectiveness of different treatments, such as a drug treatment. So you can see in this case, we've got some cells that contain our SOD1 protein and without any drug treatment, we see the formation of these large protein clumps or aggregates within the cell. However, when we expose the cells to some drugs, they are no longer any visible aggregates within the cell. So once we assess the effectiveness of treatments in our cell models, we can move on to a pre-clinical model of the disease.  

Now, there are a number of preclinical models out there that we could recapitulate MND pathology, and together with our cell models they give us a better understanding and a bigger picture of what's happening in the disease. So now I'll hand over to my colleagues who will go into a bit more detail about the work we are doing with some of these models and how they help us understand what's going on in MND. Thank you for your attention.  

Dr Jeremy Lum: Hi, my name is Jeremy Lum, and I've been a postdoc in Justin's lab for the past three years working on to investigate new therapeutic options to prevent the protein aggregation that Natalie was talking about. So, as Natalie said, the within motor neurons, there's hundreds of millions of proteins in the cell constantly being produced. And the one protein that we're particularly interested in is this SOD1 protein. And when it's produced in newly synthesised, it kind of comes out a bit like a blind piece of paper, like Natalie said. And it requires intricate folds like origami to produce the final fold in functional form.  

However, in MND, when there's a mutation in this SOD1 gene, what happens is the protein is more likely to misfolded, and that's an intermediate to form these big large aggregates. And it's the accumulation of those aggregates that we believe causes motor neurons to start to die. So of late in the ALS field, there's been this drug called CuATSM, which has garnered quite a bit of interest. Now the reason for this is it is thought to stabilise the misfolded SOD1 protein and prevent it from aggregating. So some work for Natalie and Madison Yerbury, Justin's daughter, used the motor neuron like cells that Natalie mentioned before that express our SOD1 protein. And you can say that it forms those aggregates. However, when they put CuATSM onto the cells they found that the aggregates were no longer visible. And when we quantify that, we can see that without CuATSM treatment, we see a higher percentage of cells expressing aggregate proteins. However, when treated with CuATSM, it drastically reduces.  

So following on from that, what we did was we moved into a SOD1 mouse model of MND. Now this mouse model has a human SOD1 gene in it with a mutation similar to what we observe in the clinic. And as these mice grow older, those SOD1 starts to misfolded and produce those aggregates similar to what we've seen in the dish, and they develop paralysis as well. So they become a model for us to test drugs in. And what we did was we treated these mice with CuATSM. And you can see here that CuATSM increases survival of the mice that don't receive any treatment at all.  

Now, it's studies like this that have led to CuATSM actually being investigated in human clinical trials currently. So Justin kind of went back to the back to this how this CuATSM work and based on the fact that it's now in clinical trials, he thought, well, you know, it must be doing something good hopefully. And he went back through and started to search for other compounds which may be able to stabilise that misfolded SOD1 protein.  

So some work from Dr. Luke McAlery Victoria Sheppard in our lab found two other compounds which can help stabilise this misfolded SOD1 protein. And they could tell by the telbivudine and ebselen. Now, the best two things about these drugs is the fact that they're already being used in the clinic, in the case of telbivudine and ebselen is already in clinical trials. So that drastically reduces the amount of time, if successful, for these labs to be tested in safety trials. We already know that we can deliver them to humans without too much toxic side effects.  

So what we did is we went back to our cell model and we put the three drugs on the cells to see whether they reduce aggregation. And you can see here that CuATSM, telbivudine and ebselen all reduce the amount of cells with aggregates compared to those that are untreated. Secondly, we looked at cell survival to see whether the aggregation load was also correlated with reducing that motor neuron death. And we say that CuATSM, telbivudine and ebselen all increased cell survival as well. However, then Justin had this other idea. What happens if we add all three drugs on together and we call this combination therapy. So when we combine all three drugs, we say that we reduced the amount of cells with aggregates even further. Similarly, when we look at the cell survival, we say that we increase the cell survival more than any one drug alone. So this was quite, quite promising.  

We then went back to our SOD1 mouse model of MND, and this work was done with Michela Brown, and we say that we treated the mice with either nothing CuATSM alone or CuATSM, telbivudine and ebselen being our combination therapy. And the first thing we wanted to do was test whether these mice had improved motor function compared to the untreated mice. So what we do is we put the mice on this apparatus called a rotor rod, and this rod spins around and around. And as disease progresses and the mice develop paralysis, they're unable to stay on the rod for as long. And what we do is we measure the time to fall off. So you can see here that the untreated mice aren't able to stay on that road for very long, however, when we trade with CuATSM, we can increase the time that they stay on that road. Furthermore, when we treat with our combination therapy, you can say they're able to stay on the rod even more.  

And lastly, we looked at survival of these mines, and as I showed you before, CuATSM increases survival compared to those untreated mice. But promisingly, when we add our combination therapy to these mice, we can extend their survival more than CuATSM alone and the untreated mice. So this is promising work from the lab. And it kind of suggests that if we target this protein aggregation process, we can find potential therapeutics for MND.  

And lastly, I'd just like to show this video from the 2014 Ice Bucket challenge that we held here at UOW. And I want to show this video because I think it's quite important, the fact that the Illawarra community has donated a lot of money to MND research and in particular Justin's research.  

And on behalf of Justin and the team, we really want to say thank you to the Illawarra community for those donations because a lot of the work that I've shown today was actually funded through those donations. And now I'd like to pass on to Christen Chisholm, who will be talking about how to remove these protein aggregates from the cell.  

Christen Chisholm: Hi, everyone. Welcome. My name is Kristen Chisholm. I'm a PhD student and research assistant for Justin. And as Jeremy said today, I'll take you through my work, which has been to develop a genetic therapy that targets misfolded SOD1.  

So as we've already made clear, one of the main research areas that we focus on in the Yerbury group is how to protect the cell from misfolded protein. We know that if there's too much misfolded protein, it accumulates into these insoluble clumps that we call aggregates, which end up in the death of the cell. Jeremy talked about using some small molecules to help proteins fold correctly. But for my project, Justin had a different question. He wanted to know whether we could actually remove the misfolded protein and in that way prevent the aggregates from forming. So in order to answer this question, we had two problems that we had to face.  

The first was how were we going to find the protein that we were targeting? You've got something like 40 million protein molecules in each one of your cells. So finding the right one is no mean feat. And then secondly, if we could find it, we then needed to know how are we going to remove it? So to answer the first part of this question, Justin formed a collaboration with the Canadian biotech company ProMIS Neurosciences, and they had developed this panel of antibodies. Now, antibodies are quite a useful tool for biologists. They are highly specific. So these antibodies could not just find SOD1 in the cell. They could actually differentiate between the misfolded form and the correctly folded form, which is really important for us because we want to leave the correctly folded form alone so it can do its job.  

So for the second part of the problem, we turned to one of the natural pathways in the cell. Now, as we sit here today, it's not just the people with MND who have a misfolded protein problem. We all have misfolded proteins in our cells. Some estimates suggest that up to 30% of proteins misfold. So it's quite a complicated process. But luckily for us, the cell has a mechanism to protect itself. You have these surveillance proteins called E3 ligases, which travel around the cell looking for misfolded protein. And when they find one they bind to it, the tag it and then they transport it off to this structure here we call it a protein zone. And it's a little bit like a garbage chute. You feed the protein in the top and it gets chopped up inside into these small pieces that are harmless to the cell.  

So Justin's strategy was quite straightforward. Let's take the antibodies from ProMIS, let's fuse them to an E3 ligase, and when we put them in the cell, the antibodies will find misfolded SOD and the ligase will then take it off to the proteasome for degradation. So we call that therapy misfoldUbL because it is specific for misfolded protein. In my case, that specific for SOD1 and the ubiquitin ligase pathway, the ubiquitin being the tagging molecules and the like as being the surveillance protein. So over the past three years I've been optimising this therapy. I started in a cell culture model ProMIS sent us a number of different antibodies, and I also trialed a number of different ligases. And you can see this is just a representative graph of the kind of results that I was finding where without the misfoldUbl, you can see that somewhere in the vicinity of 50% of my cells were showing aggregates. But when I put in the various misfoldUbls, I was able to reduce the number of cells with aggregates.  

Now, with that success, we decided to take our misfoldUbl into a mouse model, which Jeremy spoke about. So right now we're hoping that the mice who have both the SOD1 mutant gene and my misfoldUbl, are able to retain their motor function for longer and live longer than the mice that just have this one mutant protein. So with that, I'd like to thank FightMND, who have funded my work and the scientists who have helped me along the way.  

And just before I go today, I do have something personal that I wanted to say. I first met Justin in 1991. That was long before SOD was found, or we knew that motor neuron disease affected families, that some people had a genetic reason for it. He had just finished high school and he was going off to uni to study commerce and be a professional basketballer. And he met my friend Rachel. And not long after that, married her and had his two beautiful girls.  

Now, over the next 25 years, I watched his journey from understanding that his family were affected by this disease that we knew very little about, to trying to understand it by going back to uni, to study science, to becoming this world renowned leader in the field. And in all that time, I was blown away by his dedication, his commitment, his resilience and his intelligence. But it wasn't until 2018 when he chose to be ventilated in order to continue his work fighting this dreadful disease, that I realised how deep his strength really was. At the time, I was leading a fairly comfortable life as a high school science teacher, but I was so inspired to be a part of his fight that I decided to come back.  

To Justin today, I want to say to you that we see your superhuman strength. You have inspired all of us. You inspire all of us every day to work with you. And I know that technically you're my boss at the moment, but as your friend, I want to tell you how proud I am of everything you have achieved. And how honoured I am to be doing this work with you. And with that, I'm going to pass on to Dr. Isabella Lambert Smith.  

Dr Isabella Lambert Smith: Thankyou, Christen. Hi, everyone, my name is Isabella, and I'm going to be outlining a particularly ambitious and novel treatment idea that Justin came up with a couple of years ago. A strategy that we hope will lead to a regenerative therapy for people with MND to restore their muscle function.  

So I'd like to start by highlighting that Justin's research vision is continually evolving. Natalie, Jeremy and Christen have all outlined this process, this concept of protein misfolding and the pivotal role that this phenomenon has in MND. So understanding this process of protein misfolding and discovering ways to correct it has formed a core part of Justin's research vision. But in order to be able to save motor neurons and treat MND.  

However, regardless of finding ways to stop protein misfolding or find ways to clear these toxic proteins away from motor neurons in order to save the motor neurons, up to 80% of a person's motor neurons have already degenerated by the time that they are diagnosed. So Justin realised that in addition to finding ways to just to save motor neurons that still exist in a person, we also need to find ways to replace the motor neurons that have degenerated so that a person with MND is able to regain their muscle function.  

So as Justin's research vision expanded into the realm of regenerative therapy for MND. He came up with this idea of investigating how we can actually replace motor neurons that have degenerated and he came up with this idea of using the body's own healthy cells to regenerate motor neurons. So this is a vital research direction because even if we do find ways to save remaining motor neurons in the person and stop the progression of the disease, a person might be able to regain their muscle function without additionally receiving regenerative therapy to restore the connections with muscles that have already been lost. So Justin came up with the idea of investigating if we can use sensory neurons which are unaffected in MND to convert into motor neurons. So this might sound like science fiction, but this process of cell trans differentiation, which means converting one cell type directly into another cell type, is an area of research that has arisen in recent years.  

So this force conversion can be achieved using a combination of chemical cocktails and by modifying the activity of certain key genes. So you might be asking the question, why would we target sensory neurons for trans differentiation into motor neurons? Won't a person lose their sensory function? And is this worth it? So motor neurons are a very unique type of cell in the body. There are actually no other cell types that are quite like motor neurons. They are extremely long cells, so they connect our spinal cord to all of the different muscles in our body, and thus they can actually stand for up to a meter in length. There are no other cell types in the body that are this long and covers such a large distance except for sensory neurons. So sensory neurons are similar to motor neurons in that they can actually span up to a meter and a half in length. And they can lie close to motor neurons in the body connecting with muscle.  

So a combination of Justin's ingenuity and his strong network of collaborators has allowed us to make use of three very powerful scientific model systems to assess our strategy for motor neuron regeneration. And so this includes strong ties with Professor Lezanne Ooiy, who we will be hearing from a bit later today, and Dr. Yee Lian Chew, who is a pioneer in her field using the nematode model elegans. And so just to summarize all of this, Justin believes that we need to find ways to replace motor neurons in addition to using conventional therapies to save remaining motor neurons in people. And this is important so that a person with MND will be able to both have the progression of disease slowed down in addition to actually regaining their ability to control and move their muscles.  

So Justin has been truly a pioneer in the field of MND research. He has brought together scientists from literally around the world, coming from different scientific specialties, coming together to work on MMT and to find effective ways to treat it. And he's also brought in the minds of scientists who work on MND and other diseases. And this includes his friend and fellow scientist, Darren Saunders. So Justin, throughout his career, he has challenged traditional perspectives in the MND research field and has significantly advanced our understanding of MND. And to reiterate what Luke said earlier, we all see Justin as a leader and a beacon. He has brought together and trained up so many different scientists to work on MND. And his family's journey with MND and his journey to becoming a leader in MND research. His kindness and his resilience and his generosity to all of us that he has mentored in his team are truly remarkable. And I think it's safe to say that our lives and our perspectives have been changed for the better because of him. So thank you, Justin. So I will now pass on to Senior Professor Mark Wilson. Thank you.  

Senior Professor Mark Wilson: Hello, my name is Mark Wilson, and I'm just going to give a brief talk today on one of our major projects, discovering new drugs to treat motor neuron disease and researching amongst Australia's unique flora and fauna. And this project was originally inspired by an ex PhD student. He's shown here second from the right. So it's Justin around about 2005 and two other students, Amy White on the left and Alyce Stewart on the far right. And that's me looking somewhat bemused on the second from the left.  

So Justin was quite an outstanding student, both committed and talented, which is a rare combination. And here he is at his graduation wearing a funny hat in 2007 and his PhD thesis 'Characterisation of novel extracellular molecular chaperons and their effects on amyloid formation' gave him the basic grounding in studies of protein folding and chaperons, which led him to then go on to his focus, which is stayed with him of motor neuron disease, which involves spreading aggregation.  

So some of the other talks may have introduced this already, but in motor neuron disease, insoluble lumps or inclusions of protein appear inside the nerve cells that are joined to muscles. And when these inclusions shine now by the bright green circles inside the nerve cells appear, it leads to the eventual death of the nerve cell and consequently of loss of control of muscles. Okay, so yes, nerve cells die, you can't control your muscles anymore, pretty serious pathology.  

So we use a cell model which is transfected, meaning it has a gene introduced to express a particular protein that is found commonly in motor neuron disease. And that particular protein is called TDP43 and TDP43 we fuze it, in other words, connected in to end with a fluorescent protein and we use this and express it in cells and the little video here shows a cell rotating in three dimensional space and the bright green lumps the inclusions inside the cells so we can make cells express this protein and they form the inclusions. And this has bad effects on the cells themselves. So we use that model as a way of searching for compounds that would reduce those inclusions and lessen the pathology associated with motor neuron disease. So we grow those cells in 96mm plates, plastic plates, tiny little wells, and into each well we add different drugs or extracts from plants or animals, and then we grow the cells for about two days, and then we break the cells open. So we then analyse how many inclusions have been formed inside the cells. And to do this, we use a technique called flow cytometry. And basically you burst open the cells with a detergent and then then you put the = lysates the solutions with this with the disrupted cells through a flow cytometer and we are searching for like this dog is looking for a particular type of drug, we're looking for drugs that reduce the number of inclusions formed in the cells.  

And an unusual feature about this particular project is that we access fractions, chemical fractions that are being prepared from natural Australian native plants and animals. And there's a thing called Nature Bank, which is up at Griffith University in Queensland that provides all of these, like libraries of extracts from different types of plants and animals, and so we screen literally tens of thousands of these extracts looking for those that might reduce the number of the inclusions in the cell model.  

And this is just some data showing a plot on the left top here and the red circle represents three fractions that we screened that have substantially reduced the number of inclusions. So the percentage of inclusions of the control is shown on the Y axis at the left. So the other fractions to the right that are not encircled with a red circle, just a variety of other fractions that do not reduce the number of inclusions. And so they're running in around about a 100% level, whereas the three inside the red circle are down at more like sort of 30 to 40%, so quite a lot of reduction.  

We then took one of those fractions in the red circle and had it chemically further separated and then retested it. And the plot on the right shows different fractions from that secondary separation. And then they tested in the same assay in the same way. And you can see that fractions 54 and 55, these ones down here show a very marked and dose dependent reduction in the inclusion numbers. So and this particular fraction comes from a marine sponge. And so we're continuing work on this to try and purify and get the specific compound from that marine sponge that has this activity. So that's where the the arrow shows where you have the decrease in numbers of inclusions. So this project is continuing and in this year, 2023, we have new funding for it from both MND Research Australia and also from Takeda Pharmaceuticals. And we are continuing this search and and hope with luck to find a pure compound or maybe more than one that perhaps can be translated into an effective treatment for motor neuron disease. And so to go back to the beginning, this was inspired by Justin himself. Thank you. = 

Professor Ron Sluyter: Thanks, Mark, for that presentation. I’m Professor Ron Sluyter and I'm delighted to talk about our work with Justin on motor neuron disease and to also take this opportunity to publicly congratulate him on a magnificent career to date, including the publication of his forthcoming book.  

If memory serves me right, I first met Justin in spring of 2009, and shortly after he came into my laboratory with some excitement showing me this article on motor neuron disease and on purinergic signalling, which was the focus of my research. This article was from Cinzia Volonté in Italy, a name that I'll come back to later.  

This article, as well as other articles at the time, highlighted the fact that if you activate P2X7 on brain cells such as microglia and astrocytes from mice with motor neuron disease, this could cause the release of unknown factors, which in turn would induce toxicity in motor neurons, which then has the potential to drive MND progression. As a result of this study and others at the time, Justin and I decided that we would look at this pathway together in motor neuron disease.  

And so we recruited a talented research student. Rachel Bartlett who is now Dr. Bartlett, and as you've seen from earlier presentations, is still in Justin's lab working. As part of Rachel's early research, she confirmed that microglia cells express P2X7 and that it's activation can cause the release of reactive oxygen species, which may be responsible for inducing motor neuron death. This research that we did previously with Justin is really just an example of his incredible ability to work with other UOW researchers to raise awareness around motor neuron disease and to really develop a critical mass of MND researchers here at Wollongong, which Luke highlighted earlier.  

In addition, Luke also highlighted the fact that Justin's had many national and international collaborations, one of which was with one of which is with Professor Neil Cashman from the University of British Columbia. If memory serves me right, I believe Justin tracked down the Neil Cashman at the airport after a conference one year to discuss this idea of propagation of protein aggregates going from one motor neuron to the next. And so together they've done a number of years work on that subject. And Luke alluded to that previously. What wasn't known at the time was how these protein aggregates could be released from motor neurons. So Rachael Bartlett in our group continued to look at these P2X7 on motor neurons to confirm their expression on these cells. And then as these cells express protein aggregates and you activated P2X7, you could get release of these aggregates. More importantly, Rachael showed that these aggregates could be transferred to nearby motor neurons where they would induce cell death and promote motor neuron disease progression potentially. In addition, these aggregates could also be taken up by neighboring microglia to cause the release of inflammatory mediators, which also have the potential to drive motor neuron disease. With Rachel Bartlett, we then went on to undertake the first preclinical drug trial of MND in mice at UOW, and this work laid the platform for other studies that Justin's team has talked about earlier today. In this study, Rachel treated mice with a nonselective P2X7 antagonist and could reduce motor neuron disease. At the time of our study being completed, two other studies were published supporting this idea that if you block P2X7 with drugs, you can prevent motor neuron disease in mice. This then led us to try a second P2X7 drug, one that was more selective and more potent. And this work was conducted by Dr. Diane Ly, a UOW graduate, and at the time a research fellow in our labs to undertake the study. This study that Di completed, along with another one that was published from a different group, collectively, showed again that if you target P2X7 that you can reduce motor neuron disease in mice. However, it highlighted the importance of dosage and starting points of treatment.  

And so just in conclusion, the work that we've done with Justin over the years has been internationally recognised and we've recently completed a book chapter with Cinzia Volonté, who opened the field to P2X7 to motor neuron disease and motor neuron disease to P2X7. And this chapter, as well as future work, will continue to explore the role of P2X7 purinergic signalling in motor neuron disease and hopefully contribute to finding a cure for this disease. So thank you for your time and I'd now like to introduce my colleague, Professor Lezanne Ooi.  

Professor Lezanne Ooi: Hi, everyone. It's my absolute pleasure to be able to talk to you today. So I'd like to tell you a little bit about some of the work that we've been doing on motor neuron disease as a result of Justin's influence. I first started my lab in Wollongong in June 2012 and it was shortly after that that I gave a talk at one of the centers and talked about the work that we've been doing using patient cells to understand Alzheimer's disease. And Justin and Mark came to me and asked if we could think about doing a similar thing for motor neuron disease. So we started to do that and we wrote a grant together. So myself, Justin, Ian Blair and Dominic Rowe who were from Macquarie and we received our first funding from MND RAI in 2014 to progress that work. And we started to build a library of patient cells from MND patients from the MND clinic in Macquarie at that time. So that really kicked off a very fruitful, productive and fun collaboration with Justin and his team and other collaborators from around Australia and India and internationally as well.  

So I'm showing you some pictures here that go through a little bit of the history of that collaboration. And one of those pictures is Justin and I in 2015, after we had received a big grant with some collaborators at Macquarie and of the other universities as well. I also show here a picture from 2014, which is from the proteostasis and disease conferences, including MND. So we have this very vibrant research community focused on including MND as well. And that picture shows you a picture of Olero Cartel, who's one of the world's foremost leaders in protein chaperons. And it just goes to show you that we've been able to bring these leaders to Wollongong as part of the work that we've been doing. And this amazing community that we have for research is also shown here from a picture in 2017 where we were celebrating MND research at UOW. So a little bit more about my lab, so we are the neuro developments and neurodegeneration lab. So I'm showing you a picture here from 2022, actually that was from the proteostasis meeting last year. So that was the fourth proteostasis meeting that we've had in Wollongong. But I also wanted to show you this picture from 2014. So in 2014, when Justin and I started the project where we wanted to use the cells from patients to investigate motor neurone disease, and we recruited a very talented PhD student, Monique Fax, and she started to work on those cells. And I'll tell you a bit more about about what she found shortly. But in general, our lab works on a range of different diseases, including Alzheimers, Parkinsons, vanishing white matter disease, we've also published on brain cancer and have some projects on epilepsy in addition to the work we're doing on motor neurone disease.  

And what we try to do is use cells that are donated by patients so that we can understand disease processes and for drug discovery. And we look at the effects of how genes cause changes in those cells or how cells may work together to cause processes such as inflammation and how that affects brain function by working very specifically on certain proteins in membranes, and they're called ion channels. So the concept that we were using and still use to this day is to use patient cells to try and understand disease processes. So how that works is that a patient donates their their cells. Usually it is very accessible cells type something like skin cells, and we can reprogram those cells into what's called a pluripotent state. So these cells then act like stem cells. And once we have those cells, we can convert them into relevant cell types, including neurons. We take those cells, characterise them, and then test different drugs as well as test disease mechanisms as well. Okay.  

So I mentioned that Monique started working in the lab in 2014 and we've been working for a number of years with Justin and Justin's lab. And this is one of the papers that is coming out of that work also with Natalie, who you heard from earlier, and Darren Saunders, who is also who's also been mentioned. And so the paper specifically looks at protein degradation and how it's altered in cells that come from MND patients, as well as other types of cell models that carry those mutations. And it basically shows that protein degradation is altered in cells that come from MND patients. And we think that there is a big deficit in how the cells are able to deal with those proteins to remove them to prevent aggregation. So that work is still ongoing.  

Justin and I have published already ten publications, but there's more in the pipeline as well. And with continuing the work, looking at MND using a number of different approaches, including machine learning, so trying to use computers to help us understand the differences between patient and control cells. And we're also using our cells to develop new therapies for MND, such as antisense oligonucleotides. And that work is also being followed up by trying to understand how to deliver these new therapies for MND as well. And that work is being done in collaboration with Kara Vine-Perrow at UOW, which neatly brings me to introduce Kara for the next talk. So thank you very much, and I'll hand over to Kara now.  

Associate Professor Kara Vine-Perrow: Thanks, Lezanne. Sorry about that delay. Good afternoon, everyone. It's a real honour to be here today to celebrate the remarkable achievements of a dear friend and colleague, Professor Justin Yerbury. So Justin and I have been friends for over 20 years now, and we first crossed paths as undergraduates when we were both studying science degrees here at the university. But I guess, you know, what brought us to the university to study was for very different reasons. So I was interested in pursuing a career in cancer research. While Justin was deeply driven by his personal experience and family history of MND and a drive to better understand the disease. So fast forward a few years and after we both established our own independent labs here at UOW, we've now come together and using our complementary expertise to really develop new and innovative approaches to improve delivery of drugs to the central nervous system where they're needed. And that's what I'm going to be talking about today.  

So one of the biggest challenges facing the effective treatment of MND is the blood brain barrier. So most of the talks you've heard so far are really about targeting those cellular processes. But once we've identified a target, we actually need to think about the whole person and delivering the drug to the brain and the spinal cord where it's needed to act. So the blood brain barrier, as the name suggests, is a physical barrier between the brain's blood vessels and the cells and other compartments that make up the brain tissue and as you can see here. And it's really essential in maintaining brain health. But it has a downside when we're trying to treat MND because the vast majority of drugs that we have developed so far don't readily cross the blood brain barrier. So all blood vessels in the body align with endothelial cells and you can see them here. So here's your blood vessel and the endothelial cells are shown here in purple. And I want you to imagine that these people standing alone here to line up blood vessels throughout the body. And you can see here that there are gaps in between these endothelial cells, and they're there to let molecules out of the blood vessel and into the surrounding tissue. But when we look at the endothelial cells that line the brain's blood vessels, we can see that they're really wedged quite closely together and they form what we call tight junctions. And these tight junctions are highly selective and they only allow certain molecules through. And that means it's very challenging to deliver drugs via the bloodstream to the central nervous system where they need to act.  

And so a lot of the drugs, the targeted drugs that are being developed today, including the antisense nucleotides that Lezanne mentioned earlier, they rely on very invasive routes of administration to get them into the brain and the spinal cord. And so I guess that's how the collaboration with Justin and I started really, it's how can we overcome this barrier to improved drug delivery. So my lab is primarily focused on developing, I guess, new drug delivery systems to improve site specific drug delivery to cancer cells. So this is in the context of breast and pancreatic cancer while reducing, I guess, the toxicity to healthy tissue. And so in this way, we really need to sort of think about the barriers that we might face in the cancer context. So this might include physical, biological and chemical barriers.  

And so I guess transitioning from cancer biology and drug delivery in that space to this project was not that difficult because it's just another barrier that needs to be overcome. And so Justin and I worked together to to come up with a few different project ideas. And what I'm going to be talking about today is actually some work that's been going on since about 2016. And I'm just going to highlight a couple of the exciting findings that we've got from that. So for this project, we're using a relatively new and exciting approach known as focused ultrasound, and many of you have probably familiar with diagnostic ultrasound and focused ultrasound really is not that different. So it's a noninvasive technique that uses acoustic waves in the ultrasound spectrum to selectively and focally disrupt the blood brain barrier.  

So these sound waves pass harmlessly through the bone and the tissue, and then because of the shape of the transducer, they converge on a targeted region at a focal point here. And when we inject these tiny gas filled microbubbles into the bloodstream, they circulate through the body and they enter the blood vessels surrounding the brain. And when these microbubbles come in contact with these sound waves that we've applied through the focused ultrasound, these microbubbles start to oscillate and move around and they impart mechanical forces on those endothelial cells and they temporarily open those tight junctions that I spoke about earlier. And it allows the drugs to move from the bloodstream into the central nervous system. So quite nicely what we've shown is that when we applied focused ultrasound and our lead drug formulation to the brains of mice here, we actually disrupt that blood brain barrier. And so what you're looking at here is some T2 weighted MRI images.  

And so the images on the bottom panel here are mice that have been treated with our drug focused ultrasound for 30 seconds. And those microbubbles that I was talking about, and then the top panel are mice that have received all the treatments except the microbubbles. And so we can see negative contrast here. That's indicative of blood brain barrier opening. And we can see that that directly results in increased delivery of drug into the brain within that exact region as indicated by this yellow signal. And we don't observe that in the control mice. So the drug can't get into the brain unless we disrupt that blood brain barrier. And when we quantify this, we see on average that we can increase or enhance drug delivery into those targeted regions by an average of four times, but sometimes even higher up to eight or ten times, which is very, very exciting. Importantly, all of the mice recovered when we applied this focused ultrasound. There were no behavioral changes and we saw the blood brain barrier was restored as early as 24 hours and fully restored 3 to 5 days later, which was fantastic. And we didn't see any signs of toxicity or neuro inflammation. When we looked at the brain tissue post study using various immunohistochemical analysis. So again, this was very exciting for us. So in order to translate these exciting findings, we next need to demonstrate that the application of focused ultrasound microbubbles and our lead drug formulation is actually efficacious in disease models of MND. And these are the models that Natalie, Jeremy, Christen and Isabella have been talking about earlier.  

So these mouse models that are sort of the workhorses of the Yerbury lab, we use these then to assess the effectiveness of our approach. And what we're looking for is that we can delay disease progression and prolong survival in these models. And this will probably help in the development of our lead drug formulation. But I think what's most exciting is that we can probably use this same approach and apply it to drugs that are already in preclinical or clinical development and expand the scope of treatment options for people with MND. So with that, I would like to thank the amazing post-docs, students, collaborators who have worked on this project and our funding partners as well.  

And I'd like to finish by saying that it has been a real honour and a privilege to work alongside Justin on this important project. His dedication and his passion and his tireless pursuit of a cure for MND really has been an inspiration, not just to me, but to everyone who has worked with him. And I have no doubt that his contributions will continue to have a long lasting impact on the field for many, many years to come. So thank you so much.  

What I'd like to do now is to stop my screen share. If I can get my mouse back on the page and I would like to move into a short Q&A section and take some questions from the audience. So if you do have a question for any of the panellists that have presented here today, then please add them using the Q&A function below and I'll get through as many as I can in the next and 10 or so minutes.  

So I do have one question here, and I think this one's probably for you, Jeremy, so maybe if everyone is happy to turn on their videos. I think this one's for you, Jeremy. So I have a question here from Steve Oliver, who says, 'With the drugs three, maybe better than one. But did you check whether two was better than three?'  

Dr Luke McAlary: Oh, I'll answer that for Jeremy. So that's a good question, because minimising the amount of drugs someone might take is important because too much drug of any type can be toxic. We did consider it, in fact, we published a paper on two drugs alone, CCuATSM and ebselen in 2022. And that was really the starting point for the three drug idea. And the two drugs were effective in their own right against superoxide dismutase or SOD1 based MND in our cell models.  

However, we ended up going with three because the third drug Telbiverdene it does add some effect to reducing inclusion formation and cell survival, but it also acts as a antiviral and could be potentially useful in the case that endogenous retroviruses are associated with motor neuron disease. But these are big level questions and quite complicated things that might take a very long time to answer. But I hope that answer is good enough to get you started.  

Associate Professor Kara Vine-Perrow: Thanks, Luke, appreciate that. So I guess I mentioned earlier that a lot of the work, I guess, started at the very fundamental levels of focusing on, you know, protein misfolding and aggregation. And you've got some really elegant models that you can use to assess, I guess, you know, novel treatments, but also to use to better understand the disease. But has the I guess this is open to anyone to answer, but does researching MND in this way reveal anything about other neurodegenerative diseases at all? And can anyone comment on that?  

Professor Lezanne Ooi: I can say something if you like. So I think the answer, the short answer is yes.  

So there are lots of parallels between the types of mechanisms that caused cell deaths in motor neuron disease, which obviously targets motor neurons compared to other types of neurodegenerative diseases in which other neurons are vulnerable. So it's always been a big question about what causes that specific vulnerability. But as more and more research happens, we know that there are these parallel mechanisms. So something that we know, for example, protein aggregation changes in proteostasis. Those things are big factors, not just in MND, but also in Alzheimers, Parkinsons, Huntingtons, other types of neurodegenerative diseases.  

And I briefly mentioned inflammation. So that's another area that people are very interested in, why there are these big differences in increases and changes in inflammation that appear to be contributing to neuronal death in various diseases as well.  

Associate Professor Kara Vine-Perrow: Excellent. Thank you Lezanne. I've got a question here. How useful are the animal models? Do they do they translate well to the human system? Maybe Ron could answer that.  

Professor Ron Sluyter: Yes, I can answer. Well, can we answer that? The short answer is if you base it on previous drug trials, the answer would be no. Most of the drugs that have shown some efficacy or effects in disease models have failed to translate to treating human disease. In part, that's not because the models are necessarily bad, it's just that the models that have been developed really focus on a limited branch of motor neuron disease. So motor neuron disease has a number of triggers that causes it. And so as we move forward as a field, we need to always be testing drugs in different animal models. And Justin's work and team, as been explained, it is starting to go into that direction. So as we test more mouse models and other animal models there will be greater success, hopefully.  

In addition, the big barrier at the moment, too, with some of the mouse models is that we often start treatments early before disease is known in those animals. However, in humans we normally don't start treating people with motor neuron disease until they show signs and symptoms. And so another big field that would really advance and translate animal trials to humans, to humans, would be to identify a better biomarkers so we can start treatments as early as possible. We could possibly do that in people who we now have inherited forms of motor neuron disease, but in the majority who don't, that becomes much more difficult. So I think there's just a lot of work still to be done in that area.  

Associate Professor Kara Vine-Perrow: Thanks, Ron. I've got a question here that maybe someone from Justin's team can answer. So eye movement seems to be somewhat immune to motor neuron disease. Do we understand what makes the movement different from other body movement?  

Dr Luke McAlary: Yes, that's a great question. And that really gets at one of the things Justin has strongly contribute to in the field. And he's even published a paper on this. Why is the spared so much when the rest of the motor neurons are not and we don't know 100% sure. But one of the things that Justin has suggested and provided strong evidence for is this idea that the type and number of proteins being expressed in a motor neuron is very different between a skeltomuscular motor neuron as compared to the one that is in your eye.  

So your eye motor neurons would be having a different, what we call proteome compared to the other motor neurons in your body. And it's this proteome difference governs how vulnerable that cell type is to developing disease. And we would think that the difference between these two cell types is an important area to look at, and it's something that Justin is actively pursuing.  

Associate Professor Kara Vine-Perrow: Thank you Luke. I have a question here from Ainsley. Is it helpful for a current MND sufferer to volunteer for cell donation? And if so, how?  

Professor Lezanne Ooi: The question is aimed at me. Thanks. Thanks very much for the question. So maybe if I share my email address, we can talk about that later. But yeah, happy to talk to people.  

Associate Professor Kara Vine-Perrow: Thanks Lezanne. We have another question here. Have any of the nature bank fractions been administered to mice with SOD1? I'm not sure if Mark's on the calll and can potentially answer that question or if anyone from the Yerbury labs involved in that research that can answer.  

Dr Luke McAlary: I don't think they have. But Mark is definitely saying he can't he join with video. But I think that's on the plans for Mark because I talk to the researcher working on that research, and they're going to test it in fish, worms and mice at some point. They're still working on figuring out what that drug exactly is, which should happen very shortly.  

Associate Professor Kara Vine-Perrow: Thanks Luke. So I've got a question here from Nick, and we've got a few questions that we actually can't get through, so we might just finish up on that one. So Nick is asking if there's any potential danger of opening the blood brain barrier even for 24 hours. And I guess what I can say about that, Nick, is there's been some human clinical trials specifically where they have applied focused ultrasound to patients with MND. So not applied drug treatment at all, but just looked at the safety in the context of MND patients and it appears to be safe. I don't know what the long term effects may be in terms of allowing peripheral cells in to that very privileged brain microenvironment. But the early studies tend to show that this is safe. And there's actually been a lot of work in the Alzheimers field where they're using focused ultrasound to actually ablate, these protein aggregates and amyloid fibrils to try and treat the disease that way as well. So I think there's some mounting clinical evidence to suggest that focused ultrasound is indeed safe. And certainly when you ask MND patients if they would, you know, be up for having this type of treatment, they've done the sort of risk analysis and think that it would be worth it. But there's more research that needs to happen in that space.  

Look what am I do now, unfortunately, we've got some great questions we can't get through, but there may be a way to to filter them through and for us to maintain contact after this webinar. But I will have to draw this session to a close and thank all of all of the speakers here. And we're now going to hear about one of Justin's other projects. He is a busy man and remarkably, Justin has written a memoir with his eyes. And after a short video, we're going to hear from Rosie Hunt from Affirm Press who is speaking on behalf of the publishing director, Martin Hughes. So I'll just hand over for that video now. Thanks so much. 

Rachel Yerbury: Justin and I have been together for about 31 years. We met when we were 17 and pretty early on in our relationship, a few people in the family, in Justin's extended family started to be diagnosed with motor neuron disease. Justin's had a steady decline since his diagnosis in 2016, and he's now 99% paralysed. But it hasn't stopped him from writing his memoir and also from continuing his important research into MND.  

Justin went to university to study science and went on to do a PhD and became one of the world's leading researchers in motor neuron disease research. Encouraged by Affirm Press, Justin continued to write his manuscript despite his failing health.  

Justin Yerbury: I am Justin Yerbury and this is my story. I promised my mother that I would do everything I could to find a cure. When I was in New York delivering a lecture when my thumb suddenly stopped working. I knew in that moment that MND had caught up with me. I was determined to get it all down. I hope you enjoy the book and learn more about MND and the potential of research.  

Martin Hughes: I heard about Justin's manuscript from a friend, and she asked me to have a look at it as a favor, actually. And I wasn't expecting much but, my God, once I started reading it, I was so moved and stirred and saddened and ultimately inspired. And when I heard that, Justin had written this memoir purely with eye tracking software, I just thought what an incredible achievement, we have the publish this book.  

When I read the manuscript first, it was about two thirds complete, and when I told Justin that we wanted to publish it, he became really focused and he completed the manuscript despite a lot of health concerns. He just did a phenomenal job. And the book Fighting Fate is an incredible read. The circumstances under which it was written I just cannot imagine a sharper lens on life and a greater gift than than what Justin gives us with this book, which is the gift of perspective.  

Rosie Hunt: My name is Rosie and I'm a publicist at Affirm Press, the publisher of Justin's book Fighting Fate. I'd like to read a speech on behalf of Martin Hughes, our publishing director who couldn't be here today.  

I first read Justin Yerbury's manuscript as a favor for a friend, but I immediately became absolutely gripped by this story. Justin's story has been one of heartbreak, yes, but also determination, achievement and love. And I knew that it would resonate with so many people. That he wrote the entire manuscript by using eye tracking software, illustrated his dedication to telling his story and shining a light on this terrible disease. And I knew right away that we had to publish this book. I have published hundreds of books over the course of my career, but every so often one comes along that leaves a mark on me and reminds me why I got into this business in the first place. Can you think of a more compelling reason to write a book, or imagine a sharper lens on life and hope than this? It's fascinating, it's sad, it's inspiring, but ultimately, it is a gift of perspective.  

I know the book has already had a profound impact on many of our staff who have come to know Justin and his story over the past six months. I'm sure it will have the same effect on many readers for years to come. Everyone here today will already know that Justin is a hugely talented and determined scientist. But as you will see when you read Fighting Fate, he's also an incredible writer and storyteller. He brings the reader along with him on every page, starting with the idyllic childhood in Wollongong through his schooling, years and pursuit of a career in basketball, to the moment MND came into his family's life and the immense loss and challenges Justin has faced since.  

We also get a strong sense from the book of the beautiful relationships in Justin's life, including, of course, with his wife, Rachel, and their two daughters. There are so many moments in Fighting Fate I could point to that have stayed with me, but one aspect of Justin's story that stands out is his determination to pursue research into cures and therapies for MND, even as his own health was deteriorating, starting with very little background in science and going on to achieve what he has is truly remarkable.  

You could easily forgive someone in Justin's position, or at a certain point focusing only on themselves and what they need. But reading his memoir, we learned that that is not Justin. His commitment to research never wavers, and I was moved by the fact that he has advocated against discriminatory grant assessment practices, making the process fairer for everyone.I know his story will inspire readers from within and outside of the research community to do what they can to contribute to the cause of finding a cure. It's for that reason, too, that we are pleased to be able to donate all proceeds from sales of the book to Fight MND, a foundation that does so much for the cause.  

Thank you, Justin, for sharing your story with us. It's a privilege to be your publisher and the whole team at Affirm Press is honoured to be working with you. Thank you also to Rachel for being an integral part of the process and for everything you've done throughout the process of putting this book together. And now I want to introduce a reading from Justin who has recorded a chapter from Fighting Fate. This reading comes from chapter four, A Strange Relationship with Death, and takes place in 1996. At this point, Justin's Uncle Ken had passed away with MND, but his family have not yet learned that they carry a rare genetic form of the disease.The chapter opens with Justin sitting with his 21 year old cousin, Ashley, who has just been diagnosed with MND. We will now hear Justin read this excerpt.  

Rachel Yerbury: Thank you all for coming. As you all know, Justin has seen it as his life's purpose to fight against the cruel hand of fate that he and his family have been delivered. And he's battled at every turn to research motor neuron disease in the hope of shedding light on its dark corners. In doing so, he has shone the light of hope for our family members and also for all people living with MND.  

Since his diagnosis, Justin has also fought against disadvantage and illuminated ableism as he's lived his life to the fullest and continued his research. Justin's courage to overcome obstacles, to continue working, to write his memoir, to stay with our family and simply to keep living have been victories of mammoth proportions. So thank you all for coming to support and recognise Justin today.  

I'd like to offer gratitude to Trish and all her team for instigating this event and making today happen. This recognition and celebration means so much to Justin and to our whole family, as does the support that UOW has offered Justin over the years, which has enabled him to live and work with purpose and dignity. We're so grateful to Justin's devoted lab team, who, as you've seen today, go above and beyond to keep the ball rolling on MND research. Thank you to Justin's colleagues, our family and friends and our support staff. We hope that today you have been inspired to see what can be achieved when you combine a true fighting spirit with a supportive and loving community. Thank you all.  

Professor Patricia Davidson: Thank you so much, Rachel. And what an inspiring afternoon. On behalf of all of our colleagues here at the University of Wollongong. We want to acknowledge Professor Justin Yerbury's extraordinary contribution to research his advocacy on behalf of people with a disability and the mentorship of his team and his friendship. We've heard this afternoon how Justin and his team's research has driven fundamental new understandings of MND and the collaboration across groups has been truly remarkable.  

This afternoon, I'm honoured to award the Vice-Chancellor's Extraordinary Luminaries Award to Justin in recognition of his significant dedication and contributions to research into motor neuron disease and the enormous advancements his research has produced. Rachel will present the award to Justin on behalf.  

I'd also like to thank all of my colleagues across the University of Wollongong and across the globe for being here today for this really important and impactful event. In particular, I would like to thank Justin's colleagues from the Yerbury lab and also to Jill McGarn and David Currow and team for their organisation of this Luminaries event.  

Thank you also to our audience. This event was recorded and also we will be able to send you a link to preorder a copy of Fighting Fate. Again, my sincere thanks to everyone for participating this afternoon. Kudos, Justin. You truly are a legend. We are exceptionally proud of you here at the University of Wollongong. And we send our best wishes and blessings to you and your family. Thank you.  

Daniel Hutto: Right. So good afternoon. I am Senior Professor Daniel Hutto, the Head of of School of Liberal Arts, and in the Faculty of the Arts, Social Sciences and Humanities at the University of Wollongong. It's my great pleasure to welcome each and every one of you here today, and I can still see some rolling in. Luminaries, this special series brings together leading UOW researchers, industry experts and thought leaders for a one hour conversation every fortnight. We will discover how research and collaboration at the University of Wollongong is tracking global challenges. Today we welcome colleagues in the School of Education, the School of Psychology, the School of Health and Society, the School of Liberal Arts, the School of Humanities and Social Inquiry and our own Early Start as we discuss how to embrace neurodivergence and autism in education.  

Before we start, I would like to acknowledge Country. I've just come back from abroad from a trip to Europe. And I have to say Australia is the most beautiful country that I still know of and I really appreciate being able to stay here. And in this respect I think we owe the elders past, present and emerging our greatest respects. On behalf of the university, I would like to acknowledge that country for Aboriginal peoples is an interconnected set of ancient and sophisticated relationships. The University of Wollongong spreads across many inter-related Aboriginal countries that are bound by this sacred landscape and intimate relation with that landscape since creation. From Sydney to the Southern Highlands to the south coast, from fresh water to bitter water to salt, from city to urban to rural. The University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space has kept alive the relations between all living things. The University acknowledges the devastating impact of colonisation on our campus footprint and commits itself and ourselves to truth telling, healing and education.  

Now here at UOW, we are passionate about empowering autistic and neurodivergent learners to achieve their educational and social potential. Before we dive into our panel, I'm delighted to let you know briefly about two new initiatives that are adding to what we already do.  

The first is a new Autism and Neurodivergent Alliance, in which researchers, practitioners and autistic and neurodivergent community members and their families will work together to eliminate barriers and create inclusive, neurodiversity affirming communities and learning contexts. And if you are interested in joining us, please be in touch. And there will be ways of getting in touch outside of this seminar itself.  

The second is a new partnership with Aspect, who will soon be setting up two kindergarten classes and a year 12 class on our campus here in Australia. We are looking forward to sharing research and teaching expertise together. With that done, I would like to welcome our panellists for today.  

Dr. Aida Hurem is lecturer in inclusive education at Southern Cross University. She is a well-being and belonging researcher with a focus on student experience, equity and social justice. Having specialised in autism and being autistic herself, Aida is passionate about improving experiences of autistic students and staff in higher education and school settings. Welcome, Aida.  

Associate Professor Amanda Webster is the academic program director for the Master and Graduate Certificate of Autism at the University of Wollongong. Amanda has worked for over 30 years with students and their families as a school leader, advisor, teacher, program director and certified behavior analyst. Amanda's research focuses on creating meaningful social impact and aims to support the achievement and self-determination of autistic and neurodivergent individuals. 

Carina Beattie is a developmental educator and specialist in autism. She has worked in the early childhood and education sector for 15 years, working with children up to 12 years. Throughout that time, she has developed a passion for working with children who have a diagnosis of autism and their families. Carina also has lived experiences of being a mum of children who identify as neurodivergent. So welcome, Carina. Dr. Kate Croaker is a senior clinical neuropsychologist and fellow of the Australian Psychological Society. She has over ten years experience in hospital settings, providing neurological assessments and therapy to people who have a rehabilitation and medical conditions and currently works with our UOW psychology students at the Northfield Clinic. And finally, so welcome, Kate.  

And finally, Dr. Alan Jurgens has a PhD. in philosophy and teaches at the University of Wollongong in both the philosophy discipline and for the Master's of Autism program. His philosophical work is focused on the theoretical basis of the development of social cognitive capacities in children and examining our empathetic understanding of others in regard to neurodiversity in autism. His research has examined communication differences and models of disability for diagnosis and intervention. So welcome, Alan.  

We encourage members of the audience to submit their own questions using a Q&A function, and we will try to get through as many of those as possible in the background. But I will start off by actually turning to our panellists individually and asking them some pointed questions. So if I might, just again, I think we might start with you, Amanda. Amanda, what what is neurodivergence and how can we empower autistic and neurodivergent individuals to achieve their educational and social potential?  

Amanda Webster: I'm going to start with the first question, which is what is neurodivergence? And to understand that, we have to understand that in any society, the natural thing is we have, when we look at any characteristic, whether it be height or hair colour or whatever, we have a big group of people that kind of shape that cluster and similar characteristics. So when we look at height, we have a lot of people that are in this range of height and then we have those people that are kind of outliers that are either much shorter than that group or that average, or we have people that are much taller. Well, the same thing is true and how we process information around us, whether through our senses, through our our, you know, the way that we make sense of that in our heads or whatever else. And so neurodivergence is just simply those group of people for whom process information and senses differently than the majority of people do. Now, some people process things a little differently, and some people process things a lot differently. So really neurodivergence is just that. It's processing things very differently or somewhat differently than the majority of people. So in a way, it's kind of understanding minority and majority in a way.  

How can we empower? Well, one of the things when you process things differently. Unfortunately, a lot of people don't even realise how they process this. A lot of things that happen as we grow and develop as babies into childhood and adulthood that we don't even realise we're doing in our brain. We don't realise how we learn to communicate. We don't realise that. And unfortunately, the majority of things out there kind of caters to what the majority is because it's catering to what they know. And so what we have to do to empower people to do that differently is first of all, listen and learn from them about what it is that they do differently so that we can change what we do to make sure that they're getting the right information, the right stimulus, the right guidance, so that they can learn the way. For example, if you are in a school, a lot of learning is based on people looking at the speaker and imitating what they do. Well, for some neurodivergent people, that's not a natural process. It's not a natural process. So if we know that, then we can change what we do to get their attention and make sure that they are, you know, being explicit. I want you to do what I do. Oh, okay. We just don't assume. So what we really have to do is allow people to learn in their own way, but we have to figure out what it is that they need and also not base it on what works for me or what works for you. And also allow people to do things in a different way. And I think in schools this is so important is to be flexible, to really realise what it is we're trying to get people to understand and then allow them the flexibility to do that in a range of ways. And I think and also and this is the most important empower means we have to have them have a say in autonomy. So I'm really big on self-determination, and it's really giving individuals from their very early days on ways that they can feel connected to others, ways that they can develop a sense of their own competence and their own autonomy and having choices and a voice in things. And I think that's so important with all students, but particularly with students for whom they learn in different ways than we would typically expect.  

Daniel Hutto: Excellent. Thank you so much, Amanda. That was very rich answer. I mean, there's lots there I'd like to come back to, but I think we'll move on because of the time constraints. I'd like to turn to Alan and then Kate, and I'll put the same question to both of you. Can you tell us about your current work in this area? Just give us a little bit of apprase of it.  

Alan Jurgens: Yes. So very briefly, the work that I'm currently doing in this area is I want to look at the relationship between narratives and neurodiversity and institutions. So I think there's a lot of sort of underlying aebelist narratives that structure our institutions and the practices that occur within them, especially even within schools that actually cause still a lot of stigma around being neurodivergent and a lot of obstacles for neurodivergent individuals in those environments. So I think trying to look at sort of what some of these narratives that caused the stigma and caused these barriers might be and how we can sort of alter them, which also I think requires identifying the kinds of narratives that de-stigmatise neurodiversity that empower and support those individuals as well, so we can sort of focus on the ones that are important to us and maybe try to de-focus or cast off those ones that might be harmful.  

Daniel Hutto: That's really helpful. And just a question, the do you see that as connected to the assumptions that Amanda was just talking about? And she was saying, like when we approach this as teachers, how does that play into the assumptions that kind of are perhaps ambient in the way that people think about these topics?  

Alan Jurgens: Well, I mean, in I think the most fundamental way, I think there's assumptions that underlie what we even think education is. Right. Like what is the goal of having children or adults be in any sort of educational setting? And depending on what we sort of, you know, assume that goal to be is really in the sort of structure of the way that we do things within those settings. And I think some of the ways that we sort of assume that we should be doing education sometimes are very ableist minded in that sense. So kind of looking at those, which I think really importantly requires looking across the sort of social political dimension as well, because that's a very much sort of a deep aspect to all of that.  

Daniel Hutto: Thank you Alan, thanks for that. Okay, Kate, turning to you, can you tell us a bit about your current work in this area?  

Kate Croaker: Yeah, so I currently teach the Masters level psychology students about the concepts of neurodivergence and neurodiversity. And within the clinic, the Northfield Psychology Clinic, I supervise the students to conduct cognitive assessments, and the assessments are for neurodevelopmental conditions. So our typical assessments, we look at things like ADHD, specific learning disorders, intellectual developmental disorders, giftedness. We do screening for autism assessments, but we don't do a thorough assessment for autism at the moment. Many of the students, many of our clients that we have come through the clinic are students of UOW or other students at schools or other universities. And the process of the assessment is not just to provide a diagnosis, but to look and help them to identify their strengths and their weaknesses and to identify strategies to, you know, utilise their strengths to support the weaknesses that they might have so that they can perform better in this ableist environment that we have. And. Yeah. I also conduct research in ADHD particularly looking at how we can better improve the assessment processes.  

Daniel Hutto: And do you think they have to be changed significantly?  

Kate Croaker: Yeah. I think the there are multiple problems with the assessment processes there. There are multiple ways of having an assessment. You can go through the medical model or you can come through the psychology model. Everybody does it so differently. So it where the process really of exploring what is working and what's not working, so then we can make improvements. But definitely there is difficulties with access and it's a long process, especially for adults. 

Daniel Hutto: Right. Thank you so much for that, Kate. Okay. Turning over to Aida and Carina, you're both specialists in this area, but importantly, you also able to draw on your own lived experience. So, Carina, could you perhaps talk to us about the role of teachers in recognising and honoring neurodivergent strengths in children?  

Carina Beattie: Yeah, sure. So for me, one of the biggest things that I work with my children in advocating is that the staff at the school and the teachers that are working with them accept their neurodivergence and understand what it is for them. So, you know, it's what that looks like is not comparing them to other students in the school neurotypical or neurodiverse and then putting neurotypical expectations on them. It's about developing an understanding of how their brain may differ from others and also not to categorise all neurodivergent students in the same box because they're all very individual as well. And so it's understanding the students strengths.  

So when I'm working with the teachers for my children, we meet and we organise at the beginning of the year to really understand the profile of my children as required by the teacher or they aree usually included in this process. But it's also about acknowledging their challenges as well, so we can develop tools and strategies that can support them in the environment so that they are, you know, it's a holistic approach, but it's also meeting their social and emotional wellbeing as well. So one of the ways that we have worked with our schools is really harnessing my youngest son, particularly his special interests, and utilising some of that as some strategies to really support him when he's feeling, you know, that he's overwhelmed by the environment and things like that and really harnessing those special interests as a teaching practice. And I think the other thing that's really important is that teachers and schools really need to listen to the parents to help them develop the strategies that are used in the school, because the parents at the end of the day know their child way better than anybody else, but more importantly, involving the person, the neurodivergent individual in all aspects of this. So they are at the center of any conversation that they're, you know, given those choices and control, to build this sense of autonomy and agency as well as mindset before. So yeah.  

Daniel Hutto: Yeah. So, I'm just interested in the idea of the so you were saying about the, the use of the special interests. How does how would that work out in the classroom?  

Carina Beattie: Um, so far, so I can only speak to what, how it works for my, for my own child. I do work with children as well, but it's going to be individual for everybody. So I'll just speak to my son and his special interests and his connection is with his pet chickens. So when he is feeling overwhelmed about something in the environment or the task that's been given to him, they have chickens at the school. So they utilise his special interest in the chickens to help regulate his emotions when he's feeling overwhelmed by the environment. So it's not necessarily using it in the teaching practices, but it's helping for my son, it really helps him to be able to have that time to calm and be able to reenter back into the into the classroom. There are other times where they might use it. He might write a story about his chickens instead of the task instead of the writing task that they've been asked to write. So they're utilising his that interest to motivate him in his in the tasks. Depending on the need of what it is that they've got to do.  

Daniel Hutto: Right. So it sounds like they have to adopt a rather flexible approach and then come back in on things later on. That's really useful. A concrete example I think really helps. So thank you very much for that. 

Daniel Hutto: I'll turn over to Aida, what what what does this look like, this attempt to recognise and honor neurodivergent strengths in the university context? Could you say a few words about that for us?  

Aida Hurem: Absolutely. Well, I think in the university context, I think we really have a very long way to go. And we've done a lot of work, got a lot of progress, but we really are really just still starting. So the first thing I would like to say about the higher education is more around really creating an understanding of what autism is amongst faculties. So for us who are involved in autism research and teaching, who are autistic, for us it might come naturally. And we think, yep, we think everybody might understand it. But when we start to work with, you know, others we realise that it's really still we still have a long way to go as a society. And also, of course, in that in the higher ed space as well.  

So I really like to bring it back to the basics and to say we need to build that understanding what is autism so that we can then remove any bias or unconscious bias that we may have. And I think I've been reading through the comments and someone mentioned, you know, even TV shows and things like that can significantly skew our understanding of what autism is. And so I think that that's kind of where we need to start. And then by creating an understanding, we are then able to actually create a genuine sense of belonging for our students because you know belonging is very important and it has been linked to, even in my own research, to academic success. And so once we create that, then, you know, students tend to thrive and feel genuinely welcome in the space. So that's kind of, you know, and I think once we've done that really well, then we can put strategies in place that support students. And so one of the strategies that I like to use in all of my classes, whether I have autistic students there or not, is universal design for learning. And I just feel that it should really be our approach should be about all students. And that way we are catering to autistic and non autistic students. So, you know, this is something that my students over the years have told me, particularly my autistic students, they really find that that helps them quite a lot and that really this is the opportunity to be able to unmask, if you will, to just be their authentic selves, really, really helps them. So I think so to bring it back, understanding is the first thing so that we can genuinely, yeah, include everybody, you know, in our space.  

Daniel Hutto: Thank you. Thank you for that Aida. One question I just had based on what you said, I mean, and I'm sure you you maybe can say more about this. So we talk about understanding autism, but there's a lot of diversity within autism as well. So that seems an interesting point. We need to be able to perhaps understand those diverse styles and approaches, even within that, and not think that there's just a uniform approach. Would you agree with that?  

Aida Hurem: Oh, absolutely. And I think Amanda talked about that early on, you know, and use some really beautiful analogies. We are all very, very different. And, you know, I like to look at it from my experience, I might have some probably borderline savant abilities, but then I also have some challenges. And so just because I'm so gifted in one area doesn't mean that I don't have challenges and require support in other areas. So understanding that we are all very different, I think Amanda used the height as an example is really important. So. Absolutely. Yeah.  

Daniel Hutto: Excellent. Thank you so much. And look, I'm in a swing back to Amanda now and ask a further question. So, Amanda, in recent educational policies and legislation, there's a discussion of a human rights model of practice. What does this mean in terms of education for neurodivergent students?  

Aida Hurem: It's really interesting because our National Disability Insurance Scheme, the Disability Discrimination Act, but particularly the disability standards policy for education in this country, are based on that human rights model. I will argue they don't always implement things like that, but what that means is I think Kate talked about the medical model, and the medical model is the model in which basically we focus on changing and fixing individuals with difference with disability, and it's focused on making them, pardon me, but for want of a better analogy, less autistic, less neurodivergent, making them more get rid of those things and really about fixing them. A social model, which you also hear a lot about, is about no that disability isn't about the individual, it's about the environment's failure to accommodate that individual, whereas the human rights model is really about, it's more like the social model but with some critical differences in the fact that the focus isn't just on the individual or the average actually on doing what we need to do to enable the individual to do everything they want and can possibly do in their lives. And that means not just the right to succeed, but also the right to fail sometimes to and to be, you know, have the same rights as everybody else. So sometimes we do hold neurodivergent individuals to a higher standard or not. There's you know, there's kind of historically a control factor, doesn't even let individuals, you know, do the mischievous or things that other people would do.  

But the human rights model is really about focusing on the voice and the empowerment of that individual. And it's also about, yes, we absolutely need to change the environment. We need to look first at what the environment and expectations does that need to change. And I think, you know, Alan talked about what is education about? I think that's a really good question. Are we focusing on the wrong things in education to start with? But it also recognises that within each individual that we all have little things about ourselves that maybe we do need to improve, we do need to get better and and or that may be barriers. For example, a lot of neurodivergent individuals that I deal with have really significant levels of anxiety and feel that that is a real barrier. And no matter what we do in the environment, that anxiety is still there. So the more we can help them to actually manage their own anxiety is as important as of course changing the environment, to not have those things that would trigger as much inciting. But again, there are different things that it recognises that, you know, it's about making yourself, you know, you're helping yourself to learn and grow and be your best self. But also, of course, first and foremost, change in the environment and doing what we can to focus on the things that that person needs to make a difference in their lives. And I think that the work rights is really the focus there and said we've all talked about this, but really about that person having a say, that person having the information they need to make the right decisions and the supports to express those decisions in whatever way they need to, even if they aren't really proficient. It is more a language expressing it in a different way or something like that. So it's really allowing those persons to have those those rights to experience the successes and failures just like everybody else, but to make their own decisions in their lives.  

Daniel Hutto: Thank you Amanda. Well, I'm going to move on and I'm going to pose this next question to everyone on the panel. And so maybe  we can just I can circulate around and people can give me their answers. I'll read it first, so we know how important that decisions about research and teaching shoudl have genuine representation of our community with the temples in some cases. But I mean, if we took this on a broader level and thought, what's the next step for this? And I think I'll start with Kate.  

Kate Croaker: Hello? I don't. Maybe my Internet connection went bad. I didn't actually hear the question.  

Daniel Hutto: Maybe I lost power. . So I just wanted to ask so we know how important the decisions about research and teaching that when we make those decisions, that they are made with genuine representation from autistic and neurodivergent community members and their families. We just heard examples of that. Where do you see this research and teaching going next in light of that? So where do you think? What are the next steps for us?  

Kate Croaker: I think that we're only really just starting to do this work where we are genuinely having people neurodivergent people involved in the research. So I think we need to do more of that and to look at all different aspects of neurodivergence.  

Daniel Hutto: So, do you think...what would you think would be the most important thing that we might do at University leves or in schools that would be an important change. Do you have anything in mind?  

Kate Croaker: I don't have anything particular in mind. I think that in terms of universities or schools, I think that some of the things that Amanda was talking about before, looking at ways that we can adapt the environment so that it is more suitable or helpful. And I think we need to look at the the different models that we, you know, the medical model, how we can make that fit in with the neurodivergent thinking. It's very challenging doing assessments because we need to fit to the medical model to get people the funding and support that they need. So looking I guess some of the research I'm looking at is how do we do an assessment, write a report that's in that framework, but then try and explain it in a way that's not in that framework. It's quite challenging.  

Daniel Hutto: That's very interesting, Kate. So I was just thinking there myself, given what you said, maybe it's it's also some policy level changes that take place before we can get into some of the. So at a more macro scale, before we can make the adjustments properly at a micro scale.  

Kate Croaker: I agree.  

Daniel Hutto: Aida, I just wondered what you might think about that question. I know you've given some answers to it already, but I just to kind of catch what you think now. Thank you, Kate.  

Aida Hurem: Thank you, Professor Daniel. I actually believe that I'm a big believer. Like we've included autistic population now, finally, in research and all of this, and that's great. But I think that we can really do more. I think that we need to allow opportunities for autistic researchers and for autistics in general professionals, too, to actually be involved in really big decision making processes. And I think that we need more of the autistic population in leadership roles so that they are genuinely included in the decisions around policy and around development of research as well. So that's kind of where are I think we really have some gaps and I think that we are getting there. And that's where I see research and teaching going in the future.  

Daniel Hutto: Thank you so much. Okay, Alan, what what have you got for us?  

Alan Jurgens: Yeah. So I would like to speak to this a little bit. I had gone to an event hosted by the University of Sydney a couple of months ago where this was a really central point of the forum discussion. And I think the main thing that I took away from that is again, really reexamining how deeply embedded sort of abbleist expectations are within these types of institutions. Because while we have gotten better about including neurodivergent individuals with our research in terms of co-production and you know, it's inevitably that you'll find some neurodivergent researchers at universities, some of which might be working on this research. Those sort of professions, you know, research within academic institutes are still very much something that is sort of exclusionary towards neurodivergent individuals, partly due to policies around workload expectations, around lack of support for them in those institutions. 

I think we can probably see a similar thing going on even outside of tertiary education in primary and secondary education. I mean, right now everything you hear about that is the the lack of teachers and the lack of support for teachers to stay in that profession. Well, if you're a neurodivergent individual who, you know, faces difficulties and additional obstacles and burdens, then on neurotypical individual, it's going to make staying in that difficult profession even harder, right where your personal expertise would be even more useful. So I think, you know, when I talk about the need to look at those sort of ableist narratives that underlie a lot of the practices and policies that we have in our institutions, that's one of the things that I think, you know, we really need to look at is how sort of the expectations we set in not just research and teaching professions, but in a variety of perceptions, still creates barriers for for people who might be neurodivergent or disabled in general in any sort of way. Right.  

Daniel Hutto: So thank you very much for that. I'm going to ask Carina what her take on this is as well.  

Carina Beattie: Yeah, sure. So I think I agree with everything else has been said so far, but I think one of the things that we really need to be mindful of is that when when we're working with teachers, they don't always necessarily know the information that will help individual children. So it's really about empowering parents to advocate for their children and what that could look like in a school environment and some education around that for both parents and and teachers and school staff and what that can look like in our research. You know, the way that we're teaching our teachers to be able to support the children is in part it's it's giving them the information that they need to support our children.  

Daniel Hutto: So educating the educators.  

Carina Beattie: Yeah.  

Daniel Hutto: Very good. And I'll turn finally to Amanda and I'll get your comment on what you think where we want to go next in teaching and research, what the priorities are.  

Carina Beattie: We're talking about education specific, which is what I'll focus on. There's a couple of things being said, first of all, Aida talked about greater role in leadership. And I do want to point out that South Australia has just announced a minister in their area and one of our colleagues, Dr. Emma Goodall, who's an autistic researcher, just left the cause of partnerships to actually be a head researcher and lead in that office, which is fantastic at a government level that's just been announced recently. So I think that's a really positive thing. I've seen more ideas of that, but I want to go back to where I think we need to be going to something Alan said again, and I think we need to be focusing in two big areas in regards to education, what is actually looking at education in general. And Alan I once said something about what is the aim and what are we focusing on. And I think a lot of the structures that are currently in education in general are not conducive to the things that are happening. For example, Carina mentioned, you know, not every teacher can learn everything that they need to know. Are we still There's no way you can do that. What we need to do is find better ways to allow teachers and parents to collaborate. And right now we don't have good systems and structures to do that. We don't have good systems and structures both within health, with therapists and within schools to get that kind of information going.  

We've got a lot of focus on getting standard stuff at my school and not enough allowing teachers to have the flexibility to feel that they have the freedom to bring those social emotional skills. They're getting too much pressure to do academic. So one area we need to look at, I think, is in education in general. And this would make education better for lots of students. The second one, I think, and this is something that I'm going to be working on and I've been talking to Aida about, is really learning more from autistic neurodivergent individuals about how we construct learning experiences that support them. And right now we know a lot about learning theory. We don't know a lot about neurodivergent learning theaory. And so personally, that's something that I plan on looking at a lot more. And also how can we use that not just in school settings, but in therapy settings rather than using that intervention model? Let's talk about what we know about how we get people to learn and how we get them empowered to be lifelong learners. And I think that's what we need to be really focusing on. And also how we're maximizing what's already there. So for early childhood, rather than just sending everybody to early intervention where they go to a therapist and things, why aren't we maximizing early childhood programs as a platform and then expanding on that with other services and stuff. So I think there's a lot of areas in core practice that we need to look at, but also we need to learn more from neurodivergent individuals about how we can construct these things in ways that will make the best sense for them and I would say impact a lot of other people as well.  

Daniel Hutto: Right. Thank you so much, Amanda. That's excellent. Thank you all for for being able to address that. I'd like to now spend the last bit of time that we've got, maybe just picking up a few questions from the audience. I'm pretty sure, in fact, I won't get all of them. I'm looking at the Q&A. There's a good number there, but there's, I think, plenty more in the chat. But it may be that we'll be able to respond to some of those questions outside of the actual seminar itself. But let me just turn to some that are prominent here. I'll throw them open. And as long as we don't step on each other's toes too much, I'll make that more of an open mic maneuver. So perhaps you might want to nominate if you if you're on the panel, you'd like to if you think this is a question you'd want to come in on. So I'd say one of the first ones here, and I think it touches on several themes that we've already raised and maybe makes it a little bit more concrete where these things might, we're more thinking might be necessary. The first question comes from Emma Grimer, if I have pronounced that correctly, what is the process when advocating for support for teacher aides in mainstream education in primary schools to ensure the needs for the neurodivergence is met? Anyone got an opinion on that from the panel?  

Amanda Webster: I can certainly answer that. I don't know if Aida wants to, but I'm going to answer that with throwing something else back. That's actually an area I work in a lot. But the main thing that we need to be advocating for is not necessarily more teacher aides. It's the type of strategies that need to be implemented and then we can advocate if we need teacher aides to do that. What we know, by and large is that a lot of teacher aides are not being used in the right way to actually empower or enable that. What we're doing is often creating dependance on teacher aides rather than empowering the individual. So what we need to be doing first is to make sure that we're talking about the ptogram or strategy that's needed, and then we use that as a form, say, yeah, to do that we need some teachers aides or we need a computer. What are the alternative things? So we need to talk about programs and strategies first and teacher aides as a resource to do that. Second, all too often it takes as far as you know, there's a lot of things going on with helping teachers to have more knowledge, but ultimately helping teachers to have more knowledge to direct the teachers aides is a more effective strategy.  

Daniel Hutto: Right. Thanks for answering that for us. Amanda, I was just going to bring in Aida if she had any more comments on that. But if not, I'll move to the next question. Aida, do you have something you want to add?  

Aida Hurem: No, that was just perfect. I couldn't agree more with Amanda.  

Daniel Hutto: Fantastic. Thank you so much. I'll try another question here from if I forgive me if I mispronounce this Sahar Kurami. And this, I think, did touch on several of the things that people were pressing for. What is the balance between providing opportunities for individuals to learn in their own way, but also required to meet the requirements of the workforce and in their field of study? So how do we, I suppose, balance that out with the needs of what is likely to be a push for outcomes that are standardised and yet at the same time individualised in the form of teaching. So who would like to jump in on that?  

Alan Jurgens: But I mean, maybe say some of my thoughts regarding that, which would just be one that, you know, it's a difficult process to always, you know, have some sort of standardisation, especially in regards to certain specialty professions that require standardisation for things like safety. But I think also, you know, it's sort of a two way street in the sense that we also need to sort of think about changing some of the expectations within professions. I mean, that was sort of the point that I was trying to make regards to making sure that there's more neurodivergent researchers doing research. It's not just about, you know, making room for them, but it's actually changing the expectations of what's required of a researcher so that there is room for them. Similarly, we can think about that in regards to other types of professions as well.  

You know, the idea that the requirement is this, you know, a 30, I'm American, I wanted to say like a 40 hour work week is something that should be standardised and everyone should be capable of doing is maybe, you know, problematic in itself, that that expectation is a sort of ableist expectation and that we have to sort of change that. So there's I think, some room in there about thinking about how we want to sort of change the expectations required for certain professions. Obviously, you know, there's some limitations regarding the professions themselves, right? We still want to have standards for things like doctors and emergency workers and engineers. But I think there's room for give and take there. And that's where it's important to sort of analyse and understand, you know, where are these standards actually coming from and what's the motivation behind the standard, just like we would indeed, looking at education. Right. Like, why? Why is this the standard and should continue to be the standard, Right.  

Daniel Hutto: Okay. Thank you. Thank you, Alan. I'm going to throw open another question. This one, I think this is not a proper name from anonymous attendee. And this question is, what is the general position on recognising individuals, who use self-diagnosis via online resources? So does anyone have any comment on that?  

Kate Croaker: I guess I could comment. I think people can utilise self-diagnosis. There is no need necessarily to go and have a formal diagnosis unless you want to get formal services, which is where you're going to require it because they won't accept a self-diagnosis. But yes, self-diagnosis is perfectly fine and there is not necessarily any reason to go and get a diagnosis except for getting formal support or if you want to interact with a service to get some suggestions and strategies and supports. But you could potentially do that without a formal diagnosis as well, just depending on the service.  

Daniel Hutto: Okay. Thank you so much, Kate. Thank you. Okay. I'm going to move to another I'm going to see how many more I can get in before we come to a close. Madini Maha asks, what is the difference between autism and neurodivergence? What are the supporting strategies for neurodivergent children in preschool? Anyone want to give an indication here?  

Amanda Webster: I can answer that if nobody else wants to. The main difference is autism is a very specific form or aspect of neurodivergence, but there's a lot of other neurodivergent forms of neurodivergence such as, you know, people with attention issues, people with learning differences, dyslexia, things like that. So there's a lot of different forms of people that think and feel differently, autism is just one of those. How we can do things in preschool is kind of a a challenging thing. I think, again, preschool in the best sense actually lends itself really well because preschool should be about exploring and explaining things. I think the the real challenge with children in preschool is presenting things in a different way and also sometimes putting up some additional structure. So, for example, I've been to preschools that it's, you know, kids just kind of free flow and choose what they want to do, etc.  

Well, sometimes for some individuals you need to put up some structures. Like when I was working at preschool, we would have centers where, you know, there was only so many slots, and if those slots were full, you had to go to another center. So we didn't get people crowded or I had little placemats on the floor where people would sit so they can sit on top of each other. Now, that didn't inhibit their choice, but it gave them some additional structure where you could put things up in visuals that get visual diagrams or things like that, so that how things present a visually as well as orally. You might have a lot of preschools are going to, for example, have a little picture where things where things go and those are really supportive or, you know, they have little cues for when you come to the circle time and when you're in circle time, you can sit on the map or you can sit in a chair. So again, it's that sort of balance of flexibility to do things two different ways, but also some additional structures and supports there to support people who process things in different ways. And I think one of the biggest things for children in early childhood is promotion of communication in different ways and whether visually, through gestures, through objects or through words.  

Daniel Hutto: Okay. Thank you Amanda. This is a rather longer question, but I'm going to throw it out. It comes from Melissa Murphy and she writes, I'm not sure which professional this question is best suited to. We are currently teaching a modified version of the PALS program at our preschool and a parent of a neurodivergent child has raised this as a possible concern. We do modify this program already and are happy to do further, but wonder what other professionals think about teaching social skills and emotional regulation programs such as the zones of regulation in easy settings. And thank you. So she throws that open. Who would like to maybe come back on this?  

Amanda Webster: Certainly. I think that one's going to come back to me again. And I'm probably the one that knows those terms the most. Look, I think it depends on what perspective you're coming from. PALS is a good program. I don't know what the person's concern was, but, you know, there may have been a valid concern in how it was being done. I think that teaching social skills, of course, in preschool is important, but it depends on how we're teaching it. And I will argue that some of the programs that focus on emotional regulation self-regulation are all from a neurotypical standpoint. They aren't from the standpoint of the child, particularly or specifically the neurodivergent child. And sorry, I'm probably going to get in trouble for this. But zones of regulation which is very popular program, for example, actually has no real research behind it, supporting for autistic or neurodivergent individuals. And actually, I have very concerns about how it's done. It doesn't really approach the reasons and a lot of self-regulation programs, the other problem that I personally have seen with it is a lot of times they don't validate the feelings and I've seen them used a lot and I'm not I'm not saying you're doing this, but where the child is very angry and they're angry for a good reason, and they say, Oh no, you need to regulate. You have regulation problems. You know, you need to listen to him. He's mad because this happens. So I think sometimes those programs are used to invalidate and diminish the person rather than to actually listen to and validate those feelings. So right now, I'm seeing a real overuse of those words regulation, self-regulation, emotional regulation. And I think it's it's not so much them. It's how they're used. Whereas what we really want to be doing is having things that we really teach children to be aware of their body and what their body is doing, being aware of what that means and being aware of what they can do. If I'm feeling too tired of feeling too energetic, what can I do to change myself and to empower them to take action for themselves and recognise their own strengths, their own body signals. And I think that's where we want to be focusing and of course, to connect with other children that they share interest with and to, you know, do things in a way that works for them with other children and not making all children always play together and things like that.  

Daniel Hutto: Okay, Thanks. Thanks again. I'm going to turn now to a question from Jonathan Allen. He writes, Apart from assessment ILP's and building that relationship with families. What other strategies would you recommend that can empower neurodivergent students at the secondary education level? What more could be done here? Anyone have any thoughts?  

Amanda Webster: I don't want to be answering all of these, but I can answer it. A lot of these are education specific, obviously. Look, Johnathan, I think I think a strategy that I would love to see in all high schools for all children. You know, as a parent of two grown children that went through high school, you know, I would have loved to see my kids do this. I would love to have all kids have sort of their own little goal setting passport tool where they they're continuing documenting and reflecting and they're getting opportunities in class, link their strengths, the needs, what they need people to do to support that, what they want to be learning and how they're going to take strategies, goals.  

They have sort of a a self planning self determination tool that they're using and modifying it as they get a little older to start to really plan toward their school exit. That to me is so empowering. And yet we don't do this enough with anybody in high school. And then what happens is they get to about year 11 and we go, okay, so what do you want to do when you leave school? And they look at us with blank faces. So I think the more we get them to be sort of in charge of that, what is it I'm going to be able to do? What is my plan? But we can also and build it into lessons. You know, I've got an essay. So what's my plan for that? How am I going to put that out? Oh, what's an area that might trip me up? There's lots of different ways that we can build that in every day. And in classes and I think secondary school is, well, you should be doing it all the way through, but secondary school, it's really paramount.  

Daniel Hutto: Thanks. Thank you, Amanda. I'm going to I think this would probably be our last question that we'll have time for. If we have an answer, I'm going to turn to one from Jemele Stephenson. What forms of support can we give to children who have no official diagnosis and so cannot access third party support like OT and etc.? Anyone have any views about that? Amanda.  

Amanda Webster: I assume they're talking about in school, but are they talking about in general? Do you know? Well, in school, there's all kinds of things we can be doing that like universal design that Aida mentioned that there's lots of things in school that doesn't matter if we have an OT or things or official diagnosis that we can use. In fact, the Australian curriculum says that we can modify and change it, it is not dependent on a child to have a diagnosis. There are many children out there from other groups, you know, immigrant groups, whatever that need support as well. At home, I think there's so many things that parents can be doing, and I know that we've been looking at this within some of the groups I'm running. You know, the parents can be doing it. I don't mean sitting down and teaching lessons to your child every day.  

First of all, I think that's very hard for most parents. And I speak as a parent, I'm talking about, you know, having your child have experiences where you think, okay, well, I'll make sure that I give these couple of little questions before we go or I'll give them this little thing to jot down some notes to take pictures or, you know, it's really knowing what you want your child to do and how to really craft opportunities and experiences and the right feedback at the right time and the right prompt. And Carina might have a bit more on that, but there's so many things that can be done in so many environments that it shouldn't depend on the therapist.  

Daniel Hutto: Right? So me maybe a thought there is that some of the general educational practices could learn from a bit more of a tailored approach. So in that sense it could help by thinking that most of us have very diverse ways of thinking and approaching questions and problems so more sensitised we are to that the probably the better. Well, thank you for that. I think we will have to wrap it up here. So I really want to give a very big thank you to Aida, Carina, Amanda, Alan and Kate for joining us this afternoon. Thank you also to our audience. We hope you enjoyed the discussion. We mentioned earlier that we are in the process of setting up a new Neurodivergent and Autism Alliance here at the University of Wollongong. And if you're interested in joining us, please be in touch. This event was recorded so everyone who registered will receive a link to the recording via email. So I want to thank you again and please have a very good evening.  

Patricia Davidson: It's wonderful to see everyone here. I'm Patricia Davidson, I have the honour and privilege of being the Vice-Chancellor of the University of Wollongong. And it's great to welcome each and every one of you here today. Our Luminaries series brings together researchers, industry experts and thought leaders for a one hour conversation every two weeks. And today we welcome our colleagues and collaborators from a number of institutions, not just here in Australia but across the globe, and who are coming together to discuss a really important issue in how we engage diverse populations and meet their healthcare needs. And this is a very topical conversation because this week is palliative care week in Australia, where the spotlight is on the critical needs of people living with serious life limiting illness.  

But before we start the conversation today, I want to acknowledge Country. On behalf of the University of Wollongong, I'd like to acknowledge that country for Aboriginal peoples is in an interconnected set of ancient and sophisticated relationships. The University of Wollongong spreads across many interrelated Aboriginal countries that are bound by this sacred landscape, an intimate relationship with that landscape.  

Since creation from Sydney to the Southern Highlands to the south coast, from fresh water to bitter water to salt, from city to urban to rural, the University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space that has kept alive the relationship between all living things. Our University also acknowledges the devastating impact of colonisation on our campuses footprint and commit ourselves to truth telling, healing and education.  

So again, welcome everybody. Tonight we have a panel of experts and let me introduce them to you tonight. Firstly, it's an honour to welcome Dr. Dulce Cruz-Oliver. Dulce is an Assistant Professor of palliative care at Johns Hopkins University in Baltimore in the United States. She's a physician, gerontologist and palliative care physician. And Dulce's work is highly innovative because it empowers Latino family caregivers and health professionals in caring for seriously ill family members by promoting innovative research and education. Welcome Dulce to Australia, and it's fabulous to have you here on this panel.  

Also joining the panel today, we have Associate Barb Daveson from the University of Wollongong. And Barb has expertise in palliative care, implementation sciences and outcome measurement. She's the Director of the Palliative Care Outcomes Program, which is funded by the Australian Government and is a national palliative care outcomes program that aims to improve outcomes for Australians. Barb has a commitment to improving the quality of care and outcomes of patients and families, particularly those at risk of experiencing negative outcomes in care. 

It's really fabulous to have two of our colleagues here today from the University of Technology, Sydney. Associate Professor Michelle Di Giacomo is an Associate Professor within IMPACT, which is the Collaborative Research Center titled Improving Palliative and Aged and Chronic Care through Clinical Research and Translation. Michelle has a background in health psychology and behavioral health, and it's also fabulous to have with us Dr. Rayan Saleh-Moussa, who is a postdoctoral research fellow with expertise in cancer symptom trials. Her work at the moment is focused on improving the preclinical to clinical pipeline through multidisciplinary translational research, focusing on cancer symptom therapeutics. And currently, Rayan is leading a project to investigate the under-representation of culturally and linguistically diverse communities in clinical research.  

So as you can see, we've got an exceptional panel with a diverse range of experience. The format of this afternoon is that we will ask Dr. Cruz-Oliver to maybe just provide a little bit of a context of her work, which will be particularly interesting to us because we have a small population of Latin peoples here in Australia, so it'll be exciting to hear from her. And I've been hearing from my colleagues who she's already spoken to a lot of excitement around leveraging the telenovela methodology. I would also really encourage people to ask their own questions using the Q&A function. I will monitor that and we'll try and get through as many questions as possible. But now let's get started. I'd now like to hand over to Dulce who will speak to us about her research. And I'm really excited to hear, you know, how a palliative care physician uses telenovelas to improve patient care. So over to you to say.  

Dulce Cruz-Oliver:  Thank you. Thank you Trish for having me. And I want to welcome First Nations people in the audience. And it's so amazing to be here sharing my work, integrating telenovelas into hospice and palliative care for ethnically diverse family caregivers. And when I say hospice, I want to make I want to clarify that in the States, hospice is an equivalent to receiving palliative care the last six months of life here in Australia. So I just wanted to make that clear when I'm referred to hospice, is the last six months of palliative care here. Now, I would like to spend the next few minutes just sharing my story, how I came to develop a telenovela and the preliminary results of one of them. And if you don't remember anything I said, remember this, this is my headline. Video education through telenovela is a promising tool for ethnically diverse family caregivers. What this means is that caregivers need education through videos to have a better caregiving experience.  

Now my story, how I did I became interested in family caregivers was thanks to my grandma Matia and my aunt Tia. Tia was the main caregiver of Matia in the last ten years of her life, she lived until 103, and I saw Matia going through the ups and downs of being a caregiver, and she had the most hardest time for her was the hardest thing for her was to accept professional help. And it got me thinking, how can we better help caregivers keep their loved one at home? And certainly there are especially keep the loved one at home for ethnically diverse family caregivers. And certainly there are still health disparities, either because this clinical case is different, because the access of health care is different as well. Not everybody has insurance. And thirdly, because the patient provider interaction is variable. And this last factor is the factor that is modifiable and is the one that I am most interested in helping with.  

My proposal is to use videos to educate and support family caregivers, but it is specifically the video format that is telenovela, which is what Trish was referring to. So telenovela for those of you that are not familiar with that is a story. The right translation in English is soap opera. And they are very popular in Latin America. But the telenovela, the difference between in soap opera and general as the telanovelas are very dramatic and they have a beginning and an end and they they convey a message. So then I decided to use this to portray a message for family caregivers. So now I'm going to tell you how I came to develop one of them, the title of this one is 'To Care' and the Spanish version is el privelio. So this telenovela specifically I developed it as a part of a diverse supplement to the access trial. And this trial itwas a cluster randomized controlled trial that had three arms, a control arm, an online Facebook arm, and online Facebook support group. That's what I mean, online Facebook support group. Plus having the caregiver participate in the care plan meeting.  

So what I want to draw your attention is the online Facebook support group, because that's the portion of the trial that had an education component and the investigators developed original videos for this educational component. And the videos they used were video recorded PowerPoints, but people weren't watching it at all. So we decided to use this original videos and convert this into a telenovela story. And the topics of these videos were taken from feedback from family caregivers. These investigators did ask caregivers, what is it that you would like to know? or would have loved to know before being enrolled in hospice and things like that.  

So the topics where identified were self-care, lessons about hospice pain assessments, social support, shared decision making and the final journey. So we took these six topics and created this four chapter telenovela, and we decided to do a proof of concepts study. So with 39 participants from the access trials, so we used YouTube analytics to look at the viewing time and we also use the exit interviews. So in terms of the viewing time, we had 18 people that observed the original videos and we had 21 that watched the telenovela. And when you compare the viewing time, the viewing time of those that observed the telenovela, was 12% higher compared to the original videos. And when you compare the interviews, those that of telenovela had more content recalled. They also described that telenovella as very informative and they also identified follow up actions. For example, one participant reported that she did discuss the use of morphine with the family caregiver with that with the hospice staff. So think about it this way.  

The use of telenovela in a hospice setting  shows significant promise as a mode of educating caregivers. But its online delivery was suboptimal because many of them identify time constraints. So even though the viewing time of those that got to observe it was higher then not that many people watched it. So we decided to go back and ask the hospice staff how can we make this available to their caregivers? And they suggested that we show the telenovela through the hospice staff in person. They suggested we show the telenovela in person. One of the examples that they gave us was you should ask the chaplain or the social worker when they were when they are doing their visit, if there is a concern that comes up, they can watch the video and then have a discussion. So the whole point was to be to do it with the hospice staff, because in that way they have questions, they can have this discussion.  

So we took all this information and we created an intervention called novellas, the short name of telenovela. And basically this is just adding the telenovela to care to what already a hospice provides. And our theory is that by providing the information that the novella gives, it improves self-efficacy and this will reduce anxiety. So this is from Bandura social cognitive theory that links improvement in self-efficacy to reduction of anxiety. So we were able to pilot test this using a pre and post test. And this was done in the times of COVID. So we wanted to do it in person, but we converted that to video conferencing. So we used Zoom. So we had interventionists watching that with a one family caregiver watching the telenovela. So the intervention was basically the interventionist introduced to video, then they share the screen and watched the telenovela together. And then there was a discussion afterwards. And this lasted around 15 minutes each and it was done weekly. And we had our primary outcome was anxiety and we set out to recruit 55 family caregivers. We ended up recruiting 59 of those 53  started the intervention and 33 observed all four videos. And just to give you an idea, three quarters of these participants were female, mostly caring for their spouse or their parent, and they were 68% of them were Caucasian and a quarter of them were African-American.  

So I'm now going to move on to the preliminary results of this. So we looked at the first 20 interviews and basically, just to summarize that, the interviews showed that, the caregivers found this acceptable and feasible. And I want to share with you one of the quotes, 'So your video was like, make him comfortable, be able to support what is going on, but just make sure the primary objective is to be comfortable'. So we also looked at the quantitative data, meaning if we change self-efficacy, and anxiety, and we did saw that both scores went into went their right direction. It was not significant, but it went the right direction and the effect size was small. So we decided to do like a post hoc analysis to find out if any of the baseline characteristics influenced this small change. And we did find that those that observe three or four videos did better, had a significant change in anxiety and self-efficacy score compared to those that observe two or less videos. So what this means is that the caregivers need to watch at least two videos to have some benefit from the novella intervention. So I would like to close with my headline again bein that education through telenovella is a promising tool for ethnically diverse family caregivers, and that's that. I'll give it back to Trish.  

Patricia Davidson: Thanks so much Dulce. And some of the really powerful messages that I think came from your description was, you know, the power of storytelling in conveying health information, the importance of co-design and co-production. And also as we develop these interventions, we have to think about the theoretical aspects. So, Rayan, can I turn to you? Because I think, traditionally people from culturally and linguistically diverse backgrounds don't get included in many sort of traditional studies. And I think Dulce's work really targeting, in particular the Latin X population and also caregivers, who are commonly afterthoughts in many studies. Rayan, I'd be really interested to hear about your work and your study population and what has been some of your observations to really get at hard to reach groups?  

Rayan Saleh-Moussa: Thank you, Patricia. So for those not familiar, I work with the Cancer Symptom Trials collaborative based at UTS, and I'm currently leading a a program trying to understand what the barriers and enablers are of CALD participants accessing cancer clinical trials with a specific focus on the Arabic speaking community. And hopefully what we plan to do is expand to other communities. In terms of so we are still very early, early stages of this particular research, and I do welcome anyone in the audience who is a health care professional or a research staff that deals with Arabic speaking people with cancer to please contact me as we do have focus groups currently running. What I will speak to and I will have a little disclaimer. I apologise if anyone has heard me speak in the last few months because a lot of what I'm going to say is has been said before is that it's important to point out that there are many factors contributing to this underrepresentation of CALD communities. However, the literature has placed this heavy focus on the patient cited barriers such as health, literacy and language, and largely ignored the bigger picture. And that includes things like the sponsor and site level barriers, as well as broader systemic barriers. And I want to come back to those in a moment.  

But just to briefly touch on two points regarding the patient level. Firstly, I feel that we as an industry need to shift our mindset and rather than thinking of language as a barrier, we should be approaching this as a need that we are not meeting. And what that does is almost shift that unspoken responsibility. So we researchers and health care professionals need to provide culturally and linguistically appropriate support and resources to people from these communities. The second point is that this tendency to hyperfocus on language and give very little consideration for the cultural and spiritual influence when it comes to decision making around new treatments or participating in clinical trials. So individuals like myself who are from CALD communities and can speak English fluently will still have these cultural and spiritual needs that will influence our decision to participate in your trial. So, I mean, whilst translating materials or having an interpreter on hand will address the language needs of this of our communities, if your study has not taken into account these cultural, spiritual sensitivities that you wish to recruit from, then you run into some potential feasibility issues and these aspects can only be truly appreciated and addressed through early, meaningful and ongoing engagement with the community that you wish to serve.  

Just very quickly, I will provide, I guess, some key practical steps that can help us start to address this sponsor site level and broader systemic barriers. And in doing so, this will allow for a more holistic change in the Australian clinical trial landscape. So firstly, embracing diversity within your teams, be your clinical team or your research team in a very quick exercise that you can all do is survey your current research and site staff and just look at how diverse are your teams currently? Do you need to build cultural awareness and competence within your teams? What are the in-house community connections and language skills that you can leverage from and how can we provide opportunities or upskill individuals from CALD communities such as myself that work in health or research to be more involved in clinical research and academia? What are the opportunities that we can create for these individuals to progress into leadership roles? There is so much fear and mistrust towards the health and research field, and part of this is due to the lack of diversity. And in previous talks I've shared that in the Arabic community, the word for Westerner a white person is ashnabi. And if you look at the exact meaning of ashnabi, it actually translates to foreigner. So there is already this mistrust that we don't identify with people from the Western world as someone that we can trust just by using that particular word.  

Another point, a practical step would be to review your procedures and to plan ahead. So keep diversity and inclusion front of mind when you're drafting your research protocols and do not use that default exclusion criteria of non-English speaking. And when I say plan ahead, I mean, for example, work out what are the specific activities that you will need to carry out or what measures you will need in place in order to be able to recruit and retain CALD participants? For instance, you want to include community engagement activities or translation services at the site level. Clinicians and staff often report time pressure as a major issue. So perhaps you want to include patient navigators in your trial design. Another example would be to select assessment tools or patient reported outcomes that are available and translated in translated and validated versions. And they do exist if you look for them. And in planning ahead, you want to make sure that you've accounted for the associated costs and that you're including these in your funding budgets.  

So these activities and measures should not be an afterthought. It will make things a lot easier if you think of them ahead of time. And finally, community engagement is, as you as Dulce spoke about, this is absolutely critical and it is a process and it takes so much time. It takes weeks, to years, even as you know, with myself leading my current project, I need to put in the effort and time to get to know my community better because I don't represent everyone. So allow the time to engage with the community you wish to serve. Develop those strong and meaningful partnerships as early on as possible and involve the community in every stage of your research. Do not approach the community with predetermined priorities and solutions a few weeks out of submitting your grants. So take the time to listen to their needs, their priorities, and generate those solutions together. And so I guess I urge each and every one of you to go back to your teams and begin to take these very simple steps towards improving the representation and equitable access and participation of CALD communities within your research programs. Sorry, I rambled on for quite a bit. Patricia.  

Patricia Davidson: You didn't! You made some really excellent points because, you know, we often think about the health care workforce should reflect the social and demographic characteristics of the populations we serve, but we don't necessarily focus as much on what our study staff or our research teams look like. And, you know, I think you get a very powerful message that just excluding people because they're non-English speaking is a copout and it's something that we just can't really tolerate anymore.  

And again, your theme of respect, relationships and co-creation co-production was another thing coming through very strongly. Michelle, if I could turn to you and talk about, you know, what are some of the best methods to engage in evaluation or getting the voice of people from culturally and linguistically diverse groups? Dulce gave an excellent example of her study, which had both quantitative and qualitative dimensions. But, you know, I know Michelle has done a lot of work in hard to reach populations. So, Michelle, some of your methodological insights would be really useful in in this conversation.   

Michelle Di Giacomo: Sure, thanks. I think much like what Dulce has spoken about. Her approach was about a story, and that is what draws people in. And that was very engaging for the participants to watch and listen to people going through maybe what they're going through. So she spoke about making people feel comfortable. That's what a participant said. And also normalising issues that people are going through because as we know, caregivers can feel quite isolated, taking on a lot of responsibilities, having to make decisions sometimes on their own, feeling a bit well, not a bit, but very overwhelmed with the gravity of these decisions. So I think it's so powerful, the story and letting people tell their stories. So that's something I prioritise in the types of research that I do, letting people certainly tell their story what their experience has been.  

This can be through interviews, know semi-structured interviews where you might have a few things in mind that you want to highlight and get people to respond to, but also, you know, letting people progress as the natural path of their experience. Focus groups are another appropriate way for many groups to get together and talk. I think focus groups are really helpful when you want people to interact and converse and respond to each other. And it might make people feel quite a bit more comfortable rather than a one on one face to face kind of, you know, maybe less intimidating if they feel like they could speak in a group with other people who've had a similar experience. And I think Dulce also mentioned the online facebook group or support groups. And that's another kind of approach that's increasingly innovative and, you know, gets rid of the access issues and lets people join in. And I think there are positives and negatives to that approach. But it is another way of bringing the people together to enable them to share their stories and get support and learn a bit from one another. So those are some of my favorites.  

Patricia Davidson: Thanks so much, Michelle. Barb, if I can sort of turn to you, you lead this huge initiative, PCOC. Can you maybe comment, maybe give people a little bit of background who may be not as familiar with PCOC, but also, you know, maybe describe some of the strategies they can use to make sure that this very rich database is representative of the population.  

Barb Daveson: Yeah. Look, thank you Trish. And thank you for the opportunity to be here. And it's lovely to be joining the other panellists to discuss this really important issue. So the Palliative Care Outcomes Program is a national palliative care program within Australia. It's led by the University of Wollongong and the model's been replicated now in a number of countries internationally. Our primary aim is to systematically improve patient outcomes and care outcomes and we have a wonderful collaboration with the services, the palliative care services across the country to enable this national initiative. The focus is on quality improvement. We also have, as a byproduct of this national initiative, large data sets, and we are in the fortunate position as well to be able to pool together information about different culturally and linguistically diverse groups in order to start to work with different groups to progress improvements in the ways that we serve these populations. Trish a key aspect of our work is actually to also collaborate with government representatives and influence policy. And when I think about the topic today about chronic disease and underserved populations, we think about what can we do to improve policy? There are a couple of things that come to my mind, and a number of the other panellists have already spoken to this to some degree. But patient reported outcomes are key to our national program, and this is extremely important when we're looking at health systems performance metrics.  

Many countries may be focusing on process measures and utilisation measures, but we know that that does not necessarily equate to good outcomes. So in PCOC, patient reported outcomes remain key to what we're doing. Another initiative that we are enabling through PCOC and through the University of Wollongong in relation to palliative care is looking at improved coordination, collaboration and collective effort. Why is it in Australia and also in other countries that we still lack national criteria for referrals to specialist palliative care? Why is this problem about distinguishing between primary palliative care and specialist palliative care? Still, there's an elusive answer to that problem.  

So through the PCOC program and other initiatives we're looking at trying to address that in collaboration with key stakeholders. And it allows us as well as a program to move towards population based approaches. And there's been some wonderful work that's been done in Australia, in particular in the first two decades of the turn of the century. Through this, the omnibus survey in Australia, in South Australia. And what that work did was really start to illuminate some of the unmet needs and experiences of caregivers at scale. So many of the methodologies that we use to estimate need at a population level for palliative care populations are derived from disease specific approaches and they haven't yet accounted for preferences or effectiveness. And so there's an opportunity for population based approaches, and this is what we are moving towards. In PCOC, we capture about 25% of all expected deaths in the country. So we're in a wonderful position to try and move forward with progressing it at scale some solutions and interrogate some of the problems, the intractable problems to address. And of course we need to continue to do this in collaboration with experts by experience, the patients, public and the caregivers. So thank you for the question.  

Patricia Davidson: Well, thanks, Barb. And I think you've shifted the conversation in a very important way. Is that much of the research done is is disease specific, but yet really, we're living in an era of multimorbidity. And the focus of today's seminar is just not on culturally and linguistically diverse populations, but specifically those in chronic and aged care. Dulce, can I maybe ask you, particularly in your work, working with older people towards the end of life. How does culture influence the spiritual aspects and the process of living with the life limiting illness?  

Dulce Cruz-Oliver: How does that culture influence the care they received?  

Patricia Davidson: Or the care that individuals need and want?  

Dulce Cruz-Oliver: Yeah, so it does influence quite a bit specifically the way they see the health care, the way they  believe they should be, the treatment they should be receiving or not, for example. And this question makes me think of the various patients that have confided to me that, doctor, I appreciate your help, but I'm going to my home country and get healed by a specific person and I am or others that come to me and tell me that they appreciate and will take the blood pressure medication, but they they want to still take X or Y supplement.  

So those are cultural beliefs on natural things that are part of their own country and their own tradition and it's up to the provider to be open to those kind of interventions and to also be on the lookout for those that probably are harmful or that may be interacting with other medications or their treatments. But however, it's important to have this curiosity and this honesty with our patients that disease, for example, I am very open with my patients and I and I try to make do to make them comfortable in sharing this with me, not everybody does, but those that do is really rewarding. Thank you. Also in terms of religion, there are there are other factors there. But I will I will stop there.  

Patricia Davidson: I think, you know, I think it is important to think about spiritual and religious beliefs, particularly as this is palliative care week and those beliefs often become more powerful and meaningful as people enter the later stages of life. Rayan, I'd be interested in your thoughts and views on that topic, and particularly in my work with some Middle Eastern populations where disclosure is an issue and people say, 'please don't tell my mum she's dying'. How in your work, which is really important in cancer symptom management? How do you approach those complex issues?  

Rayan Saleh-Moussa: Just before I get to that, just very quickly to touch on the spiritual aspect, especially being a practicing Muslim. Just something to bring to everyone's attention in the Islamic faith, we are taught that our bodies on loan, a temporary vessel, and that we must protect and preserve in its as much as possible in its natural form. So health complications are often viewed as a test from God, but also a blessing because it's a cleansing of one's sins and that this is almost a stepping stone to the afterlife.  

Now, coming back to how do we approach these complex situations in cancer symptoms, I have not had to face these situations yet, but I guess the way I would approach it is to try and understand why the family is withholding that information. And if it is, you know, coming from a family who's unfortunately been touched by cancer one too many times, in some situations it's been because the anxiety that it would cause outweighs the benefit of that person knowing, especially if it was quite an advanced stage. And that, for instance, my grandmother, there was nothing the doctors could do for her. It was very late by the time they discovered she had cancer. So just making her as comfortable as possible and leaving it at that just so that she would not have that added anxiety towards the end of her life. So it's more about preserving whatever quality of life we could. Towards the end of her life. Yeah. So I think just trying to understand the reasons why families do not want to share that information and approaching it from that aspect.  

Patricia Davidson: I think Rayan you've given us some really powerful information. Thank you for sharing that understanding of the Muslim faith. I think that is really important to know and really highlighting the importance of, you know, understanding from a cultural and spiritual perspective why people do what they do. Michelle, can I turn to you and just maybe ask you, you know, what do you think are some of the more complex issues, particularly to engage you know, older participants. I know you did a really great study looking at widows and, you know, accessing them for research took some innovative approaches. So maybe you could share some of the recruitment approaches that you used.  

Michelle Di Giacomo: Yeah, just thinking back. It was difficult, wasn't it? We tried a few different methods. We tried just, you know, straight public advertising of the study in local newspapers and things like that. It wasn't an online based thing, but we did distribute recruitment advertisement through some large I think it was Australia policy online back in the day. And we also thought about where or who might interface or interact with older women. And I think we sent it to them through the general practice newsletter throughout New South Wales. And we got a few participants there were general practitioners read that piece in the newsletter and they knew of people, they thought of some of their patients and they thought oh, this person might want to participate in something like this. Yeah, I think it was really challenging, but I can't remember some of the other ways we went about it. It can be quite difficult, isn't it? So recruiting older people and maybe if you if you're not relying on the online or Facebook type approaches, I'd be interested to hear what other people.  

Patricia Davidson: Yeah. So Barb, from your experience, I know PCOC, you know, people are inpatient, but you've had a huge amount of experience there. How do you go about basically getting people into clinical studies that are going to represent the populations that we serve?  

Barb Daveson: Yeah, it's a really interesting question. Thank you Trish. And I suppose part of the key is to make sure that you co-design. So it's about collaboration and listening and developing methods to enable and improve recruitment rates from the get go, because you're understanding what people's lived experiences are, what their cultural barriers are. The earlier point about, it's not people that have the language problem, it's us. Without shifting our perspective to understand we've got a moral, ethical, clinical imperative to make sure that our clinical resources are translated and fit for purpose. So part of that, it's not a hard to reach population.  

It's that we actually need to immerse ourselves and try to understand people's culture and lived experiences and acknowledge that there are very legitimate reasons for why some people choose to hide their authentic self. Choose to not represent perhaps their full cultural identity or other parts of their identity for fear of ongoing discrimination and racism and other terrible things that unfortunately still happen in our health systems today. And part of the legacy, I suspect, with clinical trial methodologies and so on, is that the methodologies that we've used for our CT's and so on were developed at a time where our understanding about the importance of culturally responsive and culturally safe care wasn't as well articulated as it's starting to be now. And also the notion of sovereignty. So in PCOC, we are moving more to patient sovereignty of their own data. What about an Indigenous data sovereignty agenda where we are truly being led by some of the major subgroups in different populations to make sure that we are also operating in a safe way and informed way and a responsive way in a sensible way. So taking more of the health equity lens to every part of study design, execution, implementation and interpretation. So thinking about what we say, why we're saying it, how we're saying it. And what is left unsaid. So these aspects are critically important.  

Patricia Davidson: Well, thanks, Barb, for that very powerful answer. And I really invite people to put some questions in the Q&A for the panel. But there's already one there for you, Barb. And the question is, how should social determinants of health be considered in providing health care?  

Barb Daveson: Well, that's an excellent question. Thank you so much for whoever has volunteered the question. The services that we collaborate with and help lead the program and also remind us of the importance of holistic care and patient centered care. And part of that is actually understanding and recognising and be able to integrate into care plans and treatment the complexities and realities of people's lives. So acknowledging, identifying and, dare I say it, also measuring and quantifying so that we can address it is the social determinants of health. 

So one thing that we're doing in the PCOC program, and this will be a new collection that comes forward in the next year or so, is also making sure that we're supporting services to adequately assess social determinants of health at the start of their care journey with the service. So what we're doing is we've reviewed the ICD 11 codes and mapped out different types of social determinants of health which should align with spiritual problems. And psychological challenges that people may present with the stress that they may be experiencing from pain. We know after looking at our data for about ten year period that there's one in five or one in four reports of people that present with severe distress related to pain, that doesn't improve. In fact, it gets worse. And those trends have remained the same. And so through the integration of social determinants of health, we may actually be in a better position, both clinically and also nationally and internationally through collaborations to come up with improved models, to respond to complexity and which acknowledge people's cultural diversity and lived experiences alongside the symptoms and problems that they're that they're telling us that matter to them.  

Patricia Davidson: Thank you, Barb. I just might put a question to Dulce and Rayan, just for some of the people that have joined us today on the webinar, just might be interesting to get your reflections on how you deal with being a member of the community, having a powerful voice for that community. And also being a researcher. I think that would be really interesting. Dulce, can I start with you?  

Dulce Cruz-Oliver: Sure, being a researcher and being part of the community is something that has that is gives me privilege because and also it gives me purpose. I feel myself that I really want to serve my people, I say it that way and I want to improve it. Not only I'm part of the community, I also suffer some of the things that they also suffer in certain way. And that makes me more, more sensitive to what they mean and what they are  seeking. And so it puts me in a privileged situation. And at the same time, I have to be conscious that I cannot assume and I cannot pretend that all of them should praise me and want to help and want to participate in my studies. I have to be respectful of all that of their position. And so mainly my answer will be I feel myself in a privileged situation and in a situation also that I want to serve, to serve them and help them through my profession and through research.  

Patricia Davidson: Thank you Dulce, Rayan?  

Rayan Saleh-Moussa: Thank you. Yeah, I think Dulce perfectly articulated and captured pretty much the same sentiments. What I will add is the my husband calls me a pessimist, but there is a slightly negative side to it as well. So coming from a very big family, to put things into perspective, 250 strong Lebanese family, all based in Sydney. We have been touched by many chronic health conditions, including cancer, including neurological conditions. And I myself live with a chronic neurological condition. Having this platform and all this knowledge can be quite frustrating at times when people come to you from from the community or from your family and you can't do much to help them other than explain what their results mean, but you can advocate for them. So that's the positives. Also, I will touch on I don't think I have the right word for it, but since I've started to become more vocal on this topic and working in this research field, I have been approached by many other researchers wanting my advice, wanting me to be part of the team. And so that's something that I need to be mindful of, that I am one person and that I cannot take on all the wonderful research studies, but what I can do is refer them to other fantastic academics who will also identify from CALD communities. Because we do exist, we are out there and we are more than prepared to work with the research teams, but just to be mindful of how much I can take on as an individual because I can't solve all the problems faced by my community now.  

Patricia Davidson: So this is a question that's come about the panel's view on technology mediated methods of capturing patient data, such as patient diaries. So who would like to take that?   

Barb Daveson: I think the role of technology in the future is going to be a game changer. We've got the opportunity to do machine learning, harvesting data, looking at thresholds. I can't see reasons why in fact, there's already methodology about researchers that have analysed their own reflexive diaries during their research process. And in fact, that's assisted them in understanding why they've used certain paradigms or not. But when you think about it a meta level. And there are private companies that are already interrogating big data sets. But I suppose alongside that, it raises fundamental issues about data sovereignty, patient autonomy, choice, informed consent. So our ethical approaches to these key big questions should not be dismissed, but they absolutely need to be addressed at the same time as technology progresses.  

Patricia Davidson: Thanks. That's a great answer. And we've also got a question about, you know, how we look at subgroups. And I guess another way of looking at it is how we look at intersectionality, because our culture and language is a backdrop. But there are many different ways, you know, we have gender, we have sexuality, we have age. How how do we methodologically make sure that we we really capture those dimensions. And I think it might speak Barb, a little bit to the social determinants of health questions, so woudl you like to comment?  

Barb Daveson: Yeah, absolutely. Again, really great question. Thank you. One of the risks of dealing with population based data and big data is that we're masking heterogeneity. And so picking up their earlier point, we must not forget that every patient that comes to our doors, every family member, every community member, they are unique, they are different, that diversity needs to be respected at an individual level. However, at a population level, I suppose what we're doing also in PCOC is overcoming these traditional challenges for culturally and linguistically diverse groups or any major subgroup within the population by looking at different ways to overcome small sample sizes and problems with single institution research. 

So what we're doing is establishing a health equity program and a commitment to developing the evidence base in relation to that, in collaboration with key groups. For example, we have recently used a new classification approach when we look at all the data across Australia, 30% of people that access specialist palliative care services prefer to speak a language other than English. If we only did the analysis using that approach we would be limited. So what we've done is used, there is a meta approach where we're pulling together culturally and ethnically similar groups through a standardised approach and we are looking at good intersectionality. And what we're finding was looking at function and episodes start of palliative care, those that are older adults, 75 years or older, those that are born in Asia or Middle Eastern, North African countries and those diagnosed with neurological disease are at risk of poorer outcomes compared to native born residents in Australia. And so the intersection of these key and also population based approaches, thanks Trish.  

Patricia Davidson: Well, look, this is we're really coming to really that to the end of the conversation. And I thought I would just ask the panellists to give one take home message for the audience. Thank you so much to everyone who's participating here tonight. I'm And can I start with you, Michelle?   

Michelle Di Giacomo: I think especially coming from Dulce's work around the telenovelas, I think it's really important to take the time with people to understand their values and beliefs and then tailor according to those values and beliefs. So short and sweet.  

Patricia Davidson: Thank you, Michelle, Dulce?   

Dulce Cruz-Oliver: Mine will be use stories to help people understand and to help. The main message will be take into account family caregivers. Keep them in mind, both in research and when you are caring for patients, family caregivers are your allies, so help them as well and listen to them. Thank you.  

Patricia Davidson: Thank you. Thank you. And Rayan?  

Rayan Saleh-Moussa: I guess I'd leave you with the point, do not underestimate the power that you have to make change for generations to come by, you know, whether your research is going to improve health literacy in these populations or improve health outcomes, this will have intergenerational impacts for years and years to come.  

Patricia Davidson: Thank you, Rayan, and Barb. 

Barb Daveson: Thank you. Patient reported outcomes, caregiver outcomes, listening to the voices of the people that matter and should shape our services, do this in collaboration. And use a health equity lens to achieve positive change.  

Patricia Davidson: Well, what a amazing panel, what powerful messages for us to take home. And thank you so much to the audience. Tim Luckett pasted a link translated patient reported outcome measures in the chat box. Please access that. Thanks so much Jill, for organising us and just leaves me to thank the panel and also in Palliative Care Week. Thanks to every one for all the important work that they do to help people living with chronic illness and those who are aging. And next week is Reconciliation Week in Australia, this week's Palliative Care Week. So as we move into next week, I think we also have some important messages to advance the care for our First Nations people. So thank you so much, everybody.  

Senior Professor Sue Bennett: Hello, everyone. I'm Senior Professor Sue Bennett, the Executive Dean of the Faculty of the Arts, Social Sciences and Humanities. Thank you for joining us today for the latest in our Luminaries series, which brings together leading researchers, industry experts and thought leaders for a one hour conversation every fortnight.

Today, I'll be hosting a conversation about one of the current hottest topics artificial intelligence and how it's changing the ways we learn, teach and work. But before we start, I'd like to begin by acknowledging Country.  

On behalf of the university, I would like to acknowledge that Country for Aboriginal peoples is an interconnected set of ancient and sohisticated relationships. The University of Wollongong spreads across many interrelated Aboriginal countries that are bound by this sacred landscape, an intimate relationship with that landscape since creation from Sydney to the Southern Highlands to the south coast. From freshwater to bitter water to salt. From city to urban to rural. The University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space that has kept alive the relationship between all living things. The university acknowledges the devastating impact of colonisation on our campuses footprint and commit ourselves to truth telling, healing and education.  

Today I'm joined by Thomas King, Professor Rhona Sharpe and Professor Michael Henderson to talk about the rise of artificial intelligence tools such as Chat GPT and what that means for higher education. Some universities around the world are considering a shift back to traditional pen and paper exams to circumvent the use of AI by students. Others are focused more on what AI can help students learn while they're at university and how AI, as a part of their studies, might best prepare them for the world of work in which AI is already being used and will only become increasingly important.  

In our conversation today, we'll work through some of the opportunities and some of the challenges ahead. For the first part of our session today, I'll be putting some questions to our panel and then we'll open up for questions from the audience. Please submit your questions using the Q&A function and we'll try to get through as many as we can in the rest of the time we've got available today. So to start ourselves off, I'm going to ask each of the panellists to introduce themselves. And as they're doing so, to tell us something about what is their interest in the most recent flurry of discussions and debate about AI, Thomas, I'll come to you first.  

Thomas King: Hello, my name is Thomas King. I am the higher education industry lead for Microsoft in Australia and New Zealand. I come out of the sector, worked at three different universities in digital and cybersecurity leadership roles and spent most of my career supporting the academic and student endeavour. So hello to you all.  

Well, I think what's piqued my interest is obviously this field has been developing for a long time and, you know, we now have a product that kind of captured the world's imagination and was able to get 100 million users in two months. As imperfect as it is, and it certainly accelerated and changed a lot of conversations around AI that have been simmering in the background, shall we say, because it was always a technology that sooner come. And now obviously it's it's it's here. So yeah, in the last four months, yeah, I have been immersed in it, as the kind of hottest topic in the sector.  

Senior Professor Sue Bennett: Thanks, Thomas. Over to you, Rhona.  

Professor Rhona Sharpe: So. Good morning. Good afternoon. I'm Rohan Sharpe. I'm the Director of the Center for Teaching and Learning and Professor of Practice at the University of Oxford in the UK. Our team of educational development and digital education consultants and advisors support teaching and teachers across our collegiate university.  

And what is piqued my interest, I think, is in how our teachers have reacted to the media coverage of AI. Despite some exhaustion following the COVID lockdowns, I see teachers that are questioning and creative and thoughtful, and I'm interested in how we support their conversations about teaching and learning and assessment that prepares students for a digital world.  

Senior Professor Sue Bennett: Thanks Rhona and Michael, let's hear from you.  

Professor Michael Henderson: Thanks Sue, so a little bit about myself. I'm Professor of Digital Futures and Director of the Education Design and Innovation Hub in the Faculty of Education at Monash University. 

And I've got a broad range of interests which unsurprisingly are being shaped, challenged, enhanced by AI developments, particularly in recent months. And that goes from student creativity and creative risk taking which I am fascinated by, but also innovative education designs, including assessment and feedback. And while AI and assessment is perhaps the most commonly discussed issue and I'm going to talk about that later on this session, I am fascinated by how AI simultaneously extends our creative capabilities as learners and educators and designers, but also challenges our claims to creativity. And I think that's an interesting challenge.  

Senior Professor Sue Bennett: Thanks, Michael. And we will come to that a little bit later. But, Thomas, I'm going to come back to you for the opening question. Artificial intelligence first began to be developed in the 1950s, and it's already present in many of the tools we're now familiar with at work in our homes. But we've been hearing about it a lot more since Chat GPT burst onto the scene late last year. Can you tell us about what's changed and why it's important for the way we work, learn and both now and in the future?  

Thomas King: So I'll attempt to do a bit, absolutely. So I think what's different is the prompt and the ability to use natural language to interact with the AI. And so there's been AI that's been in use behind the scenes, whether in our products or other people's products for a number of years now. But it's the ability to make that accessible to anyone. And reducing the barrier of entry, if you will. And I remember the first time I guess a non-expert spoke to me about it was when a plumber came to do some work at my house just after it had been released, and they didn't necessarily have great writing and reading skills, and they were able to contest a parking ticket that they had and they used Chat GPT at the time to do that, and they were just blown away by the utility of it. And I think that is one of the differences, even though it's certainly not fully baked and there's lots of challenges with it, people are really seeing real utility from it and that is why it's being used. I think that's why the uptake is so large. And that's the other reason why it's kind of the hot topic and everyone's jumping into it.  

So there are thousands of AI startups that have been created to try and solve, you know, from niche use cases in individual industries to try and provide a more platform approach where, for example, us at Microsoft, we're infusing generative AI throughout our platforms and tools and we're seeing it really as a as a copilot, which you'll be in control of that help you, you know, generate first drafts of things, help you be productive and in an academic setting, hopefully give you a lot of time back. Because one of the things we have had certainly you alluded to the challenges of covid, and I think there's still evidence, certainly in the general exhaustion of workforces around the world is people want time back.  

So there's definitely an opportunity for this technology to help with that. Acknowledging all the challenges, risks and issues that we have with the technology that we need to get through.  

Senior Professor Sue Bennett: Thanks, Thomas and Rhona, if I could draw you in now, with AI becoming such an integral part of work across sectors including health, business, manufacturing, you name it, we've heard about it. How do we prepare our graduates to use it well and wisely? And how might we need to change the ways that we teach to help our students achieve those outcomes?  

Professor Rhona Sharpe: Excellent question Sue. So I think the use of AI based tools, I think of it as a digital literacy. And so I draw on what we already know about developing digital literacy to think about how to prepare our graduates, to use it well and wisely. And it's always important to remember, isn't it, that we have research and practice and experience to draw on to help us tackle these new challenges.  

So digital literacies can be understood as the ability to access and use digital tools and importantly, to incorporate these skills into contextualised practices and creative and discerning ways. So if I can just unpick that a little bit about what some of those elements are. So access is the first bit that you need to develop digital literacy. And Thomas talked about reducing barriers to entry, which is really important. So students need access. It sounds obvious, but I guess my first thing is don't ban it. The students will never develop the competencies and the capabilities that they need if they don't have access to it. And in digital literacy research over the last few decades, we've talked about functional access. So ticking the box to say that you have access to a laptop isn't functional if you share it with other members of your family and the screen is broken and the Wi-Fi connection is not very good. And we're already seeing some kind of inequalities emerging with access to ChatGPT Plus. So some students are paying for ChatGPT Plus, some aren't, some are confident in their use of language to use the prompt function that Thomas talked about. Some aren't. So really understanding what the barriers to access I think is important.  

And then in terms of skills and skills development, students need to know how to use these tools. So for ChatGPT the skill is in knowing how to have conversations with it and how to engage it in conversation. There's a great website called ShareGPT we'll share. You can go look at and it gives you loads of examples of what your team can do, and if you engage with it.  

And then the final thing is, is practices when helping students to understand when to use these tools and how to use them appropriately. And mostly I'm hearing from the students that I talk to, as Thomas said, that they're using it for productivity to improve English in emails, to learn how to write code, using it as a tutor, going back and forth and thinking about what academic productivity examples we have, I think is very important. so how did how does this change what we teach? We focus on what we always do in HE, which is to teach critical thinking, to critique an essay or piece of code created by AI, and to critique that ourselves, to critique the ways in which AI tools work to understand what they're good at and what they're not good at. To critique the way in which tech firms operate, how they're taking your code, what is the ethical monetisation of AI tools. And we must teach students how to engage critically with these tools.  

Senior Professor Sue Bennett: Thanks Rhona, we're off to a great start and building from there, Michael, I'm going to bring you in to talk about assessment because how could we not talk about assessment? So far, there's been a lot of discussion about how we might need to stop students from using AI tools to do their assessment tasks for them as a new form of cheating that we might need to combat. There's also been talk of going back to traditional exam forms, which I mentioned before, which would allow us to verify that that student has done that work. But there have also been some great ideas about how we might approach assessment differently and maybe even fundamentally change what we do. You've been thinking about AI and creativity, so I wondered if you could share some of those thoughts with us.  

Professor Michael Henderson: Thanks Sue, not a small question at all, and I'm not sure how fast I'm going to be in this response. But certainly AI in assessment, particularly around assessment security, has definitely been a very large conversation piece for myself and everywhere I go. It seems to be the thing that's talked about and which is a bit sad because there are so many exciting things that you can do with AI and generative AI in particular. But let's face it, in higher education, many of our assessment designs and I won't put a percentage to that, but I'd put a really high percentage from essays to exams, whatever formats, whether you're in particular sciences or humanities, they can largely be tackled by generative AI with outcomes that at first glance can seem to be good enough, at least for the novice. And I'd probably argue, actually, to a lot of us, when we're looking at something in a superficial, quick kind of way, if we're not paying attention to criteria of quality. So in a world of good enough, when the language shape the format, the general collection of ideas, the summary of concepts, the demonstration of proofs or solutions can all be brought together in a moderately coherent way by AI.  

Well, we need to remind ourselves about what matters. Should we be trying to avoid, limit or ignore AI or, I'm sort of here with Rhona as well in this idea of access. Should we take up the challenge then, instead of saying good enough is simply not good enough? What it produces is not something we can accept and surely our challenge to us, a heuristic that we could adopt as educators, as designers, if our educator's expertise through the application of the assessment criteria and the standards, that's part of the assessment design. So if their expertise and those criteria don't lead us to the ability to discern from raw AI output and what the students bring to the task, then we've got a problem with our assessment design, not with AI.  

So there's a tendency, I think, for us all to shy away from the sort of deeper challenge which really sort of rocks the fundamentals of what education is based on this sort of often a large mass kind of approach to assessment, production of work. And that production somehow in there somewhere represents students knowing something in a deep kind of way. So many people are talking about how to defend assessment from AI. And I'm, in all honesty, not convinced that all of our assessment design should be or in fact deserve to be defended.  

And a huge issue is that many of assessments do not allow the accurate measurement of learning outcomes. This is a problem that we've known in education for a long time. That's a challenge we all face. So to get back to your point Sue, sorry for the division, I am cautious of calls for us to go back to exams and exam halls as a way to defend against AI. Exams are not impervious to cheating. This is very much demonstrated in my own research and that of others. And more important, while exams can sometimes be useful context for the demonstration of certain kinds of knowledge, they're often not a great design for a lot of different purposes about trying to get students to demonstrate their learning. So for creative and critical thinking. So in my opinion, the call to shift back to exams is worrying. It's unlikely to stop generative AI misuse. There is already integrity issues there. It's not a solution to these things. It seems a little bit backward in the approach. Don't take me wrong, exams do have a purpose and can be useful. I'm not speaking against exams in totality, but this notion of going back somehow is going to fix it.  

In effect, we'd be trying to stop student integrity breaches by breaching our own educational integrity of the alignment between the goals and the task. I do care greatly about integrity of assessment, but there seems to be a lot of attention on quick fixes. And you know, so the ways to circumvent or exclude AI and I'd rather us think about the provocation of why should we bother assessing something that AI can do just as well or better. If we're in that situation, then maybe we need to make some big changes. Now most institutions I'm coming across, quite excitingly, accepting the idea of AI in assessments. I think it's a fantastic approach. When it first started to break the public mirror and as Thomas sort of pointed out, it's been around for for donkey's years. But it seems in this year, particularly with the prompting approach, you know, it's particularly come to the surface sort of of thinking for universities. And I think these universities have realised the futility of trying to exclude it. But wonderfully, I think about the potential of using it. And I'm finding it's quite common to hear that in institutional assessment policies. And it's exciting.  

And I think there's three ways that it can be used in general. First, we could be using or looking at how a assessment designs can consider what labors are involved that can be offloaded or co constructed with AI. So for example, communication or summary of well established ideas, why labor something that can be produced in such a way and instead allow students to engage more deeply with an idea. And the second one is we can use generative AI to support and prompt learners to use and establish outside to use established structures genres to to help with expression, to think about or to return and collate and suggest materials to stimulate the thinking. And the third is we could look at how we might use generative AI to inspire novel thinking. This is exciting stuff. We could be using it in ways to test ideas, to explore hypotheses, to quickly spin up and generate materials and notions to become a sounding board. And we could even be using generative  AI to produce comparative texts. And this is really interesting, alternative responses to suggest or to even argue with us to become a devil's advocate.  

Ultimately, it all comes down to the students ability to make decisions about quality. And that's the key thing here. Are we trying to assess the volume of content, the shape, the mere look of something? Or is our assessment, our criteria, our standards, our task and our assessors confident and capable enough to see the qualities of the work. And that's the real challenge to assessments. And I'm not sure I've got time. I'll pause it there, if you like Sue, and I'll come back on my hobbyhorse if we have time.  

Senior Professor Sue Bennett: Okay. Alright, well, we'll do that and I'll go back now to you Thomas, and just bring our discussion around to some of the tools. You sort of mentioned some of them before. Michael's talked about some of the ways they might be used and of course the digital literacy. So Microsoft and other big tech companies develop many of the tools that we use to find information, generate content, analyse data and communicate with each other. How is Microsoft approaching AI integration and what kinds of things could we expect in the future?  

Thomas King: Yeah, so thank you. So obviously we've been investing in and developing AI for a number of years. We have a division called Microsoft Research headed up by Peter Lee, and it has lots of academics who came straight out of institutions. Many still have joint appointments and they publish a lot of papers on relevant fields. So I think that's really important to acknowledge. Obviously, we have the partnership with OpenAI as well, which we've had since 2019, and I think how the vision for us is, is a few things. One is obviously there's a range of consumer type services, so we actually have a search engine called Bing, which I never really use much before February 8th when we integrated chat capabilities through the OpenAI partnership. And it has become incredibly useful and it's been really interesting to see, you know, it's only February the 8th that got released, it feels like years ago. And to actually see that product evolve on a day to day basis, sometimes better, sometimes a bit worse, but generally three steps forward, a step back kind of thing. You know, that is a way that consumers can interact, that, you know, there's no age restrictions on that one. So it can possibly be used in schools, but fundamentally changing the way we search for information.  

So, you know, the ability to do a live search with a response from a generative AI model with citations, you can have the response precise or more creative. You can even ask it for you to give the output in a blog post format or paragraphs or dot points. You can export it, you can copy it. So those things are moving very, very quickly. For most organisations, companies, businesses, universities, they'll have it in two ways. One will be we have a range of initiatives called Microsoft Copilot. So in Microsoft365, which, you know, hundreds of millions of people use, there will be a Microsoft365 copilot in which you'll be able to, you know, generate a PowerPoint from a word document, generate a word document from a PowerPoint. You'll be able to generate first drafts and to do that through natural language, but over your private data, that will remain yours. And I think that is going to be a very important way for innovation, for how organisations can get the most out of what they have and their data that is theirs and will remain theirs. And then we've got a security copilot so there's a lot of things that, you know, it'll be incorporated as a prompt within the platform, if you want to do more complex things like solve maybe big research problems or do some more custom type work, we have a cloud platform, there's a service called Azure Open AI, and it's added to our kind of AI portfolio of products.  

Not to get too much in the product, but so there's different ways that you'll interact. One will be it'll just be in the product you use and there'll be a nice prompt. One will be a dedicated sort of workbench where you can do more heavy duty things and one will be you just see it in consumer products. But you're starting to see this everywhere. Like it's not just us and the sprawl, I think is happening shockingly fast and just keeping a pace of, you know, the developments in this area and the start ups and their capabilities. I think, you know, it's reminiscent of the early web browser days or the early days where there's going to be so much innovation around this happening so quickly that it's incredibly hard to keep up with progress. So I hope that's answered the question.  

Senior Professor Sue Bennett: I think it gives us a really good sense of exactly how quickly AI is becoming integrated and how fast it's moving. And Rhona, I'd like to now build on that to come to you. And you've been interested in technologies in higher education throughout your career and in that time as technologies have developed, we've often heard about how they're going to disrupt or transform or even end education. And of course, we've had the great acceleration that we talk about under covid, digitalisation across all of the things that we do. But even when technologies appear to be new, we've often got foundations to build on, and you mentioned that early on. And in this case, we already know a lot about what makes for effective learning, what counts as positive student experience. And I wondered if you might just talk a little more about what kinds of existing research and practice that can help us understand how to work with AI? Because, as Thomas has said, it's you know, it's here, it's becoming embedded, it looks increasingly like there wouldn't be an option to say we're not going to use it anyway.  

Professor Rhona Sharpe: Thank you, Sue, for reminding me for how long I've been working in this area. I do remember the arrival of Google and Wikipedia and the panic around that. And so let's look back and reflect on some of the lessons that we learned from that. I think some of the lessons that we learned well, firstly, we learned that students weren't using it in the deep and thoughtful ways that we might have assumed that they were.  

So the digital literacy research showed that students did use Google and Wikipedia, but in superficial ways. And someone in the chat asked, 'What's the role of the educator?' And the role of the educator is to encourage students to use these in critical and creative ways, not the superficial ways that they might do without our support. So I think that's really important. And the other thing I think we learned from our experience of Google and Wikipedia is we worked really hard to understand how they worked, how you got into the top ten hits of the results in Google, how Wikipedia pages were created, and, you know, people around at the time remember all of those activities that we did with students to create Wikipedia pages themselves so that they really understood the technology behind it. So I think our approach to working with AI based tools must be based on an understanding of how they work.  

So Tracy, in the Q&A characterised large language models as synthesising and communicating information, but I think we really have to open the bonnet, we really have to look under the hood here. ChatGPT is predicting the next word or token, it's predictive text. Predictive text on your mobile. It's auto completing your word processor. It's not reasoning, it's not synthesising. It's not even copying and pasting. It's not a search engine. It produces answers that look feasible in natural language but are wrong. If you if you take away anything from the session, I think it's that ChatGPT cannot be trusted. It will give you citations, academic citations that when you follow up, they're wrong and they're not. The quotes that they drawn from these citations don't appear in the original references. It's an illusion. So understanding how these tools work and teaching students how they work is something that we can really take forward from our previous practices. I think kind of previous experiences.  

The other point that I might make, if I may Sue is about drawing on existing research and practice in the idea of teaching, learning that you're interested in. So lots of people in the chat are interested in academic misconduct, obviously, but there is an established research base and sharing the experiences of teaching learning for academic misconduct. So we know, for example, that students are more likely to present work that is not their own, that is created by another human or non-human. When the assessment tasks that they have been set is not relevant, not meaningful, when the deadlines are too tight, when the stakes are too high, and the emergence of AI doesn't change those drivers, it doesn't change those reasons why students cheat. It does reduce the barrier to entry. And so I think we have to take account of the existing knowledge base that there is to help us understand this problem.  

Senior Professor Sue Bennett: Thanks Rhona. And, Michael, I'll come back to you now and you can decide about your hobbyhorse or not. But you have touched on some of the opportunities for creative assessment design. We know in the past that new technologies can sharpen the inequalities that are embedded in ways that we don't expect. And we already know that there are some forms of assessment that advantage some students over others. What do educators need to keep in mind to ensure that we have a diverse range of assessments that is befitting of the diverse range of knowledge, skills, dispositions that we might want to assess, but also reflects the diverse range of students who we're engaging with.  

Professor Michael Henderson: Thanks Sue, another big question, I think. I think we're all agreeing. We've got to be cautious of a knee jerk reactions of sort of closing the shop of hiding away or trying to reject the existence of AI in the first place. We've over the decades have been making slow progress in improving the inclusive learning and assessment designs in higher education and in other sectors. And I think we have to be cautious of protecting that. And if we are seen to be shutting that down, if we, for instance, and again, there are there are reasons why exams can be useful, but exams also can be exclusionary of certain people in terms of differently abled and in terms of also the nature of the content and the representation of it. So we have to be cautious of the knee jerk reactions.  

And I think it's not so much that we have any new diversity of assessment forms or strategies, but simply to protect that. I think a case for inclusion and equity and I just want to come back to the topic that's already been picked up here by the other panelists. Is that generative AI can really provide opportunities for students who are differently abled to engage in ways that might have otherwise found more difficult to get through certain barriers so that they can engage in sort of on a more even playing field. Students who've got lower literacy or who are operating in languages other than English, people who suffer from chronic illnesses, all of these are cases that I've been coming across who are who are talking like Thomas's example of someone who had lower literacy, being able to successfully engage in a very meaningful task.  

Well, AI can help these people tackle sort of barriers and help us as educators and institutions to sort of become a bit more of a level playing field. Now. I think it's an exciting opportunity, but on the other hand, generative AI can sort of propagate and reinforce inequalities. And this raises two issues for me that I think it's always useful for us to keep in mind. And I'm looking at our participants and the panels here, and I feel like I'm saying the sort of obvious thing, that there are so many wonderful people here. But I think, first of all, we need to recognise that generative AI services will inevitably become a subscription service. Certain ones will be available and other ones will be limited to certain kinds of technologies but it is dependent on the machine that you learn, the Internet access you have, or literally the subscription to a particular form of generative AI. And with the highest rates presumably being connected with the most powerful services, the most natural language outputs, the most effective or comprehensive source databases, personalised responses are getting through paywall to access certain kinds of materials and information.  

And so being increasingly more context aware and the fact that these subscription services they are potentially going to replicate the same socioeconomic divide that we find in educational outcomes. And I think that's something that we really need to consider as institutions in ensuring that all of our students do have this equitable access to it and functional access as well. And also the skills that Rhona was talking about. The second issue that comes to my mind is how generative AI by and in effect become an echo chamber, albeit a very big one. It does not know the difference between fact alone, does not know the implications of biased language and stereotype representations. In its current form, it has very few values embedded, except for those of the values of the programmers and the large language model that it draws upon. And we know, it is quite well documented in various searches, you know, you might search for, you know, represent a picture of a scientist and certain kinds of ethnic backgrounds and representation, you know, gender will come back in certain ways. And so it's potentially replicating, becoming a chamber that is not productive, it's not healthy. And it's something that we need to be very critical of. So for me, those are probably the issues that I think about the most when we come to this issue of equity and diversity and AI.  

Senior Professor Sue Bennett: Thanks, Michael, and thanks everyone so far for indulging in my questions. We're going to now turn over to the Q&A and questions from our audience. And we've got lots of questions, so we won't be able to get through all of them. But I'm going to suggest that for some of them that we can sort of take them on notice and work out how we can respond after the session, perhaps through some emails. But I'm going to just pick out one that I think Rhona speaks to something that you've talked about, and that is how how do we empower students to critically evaluate the content provided by AI?  

Professor Rhona Sharpe: Yeah, I think that's something that many of us are thinking about, and I'm hearing something we haven't talked about so far very much is that potential to work with your students to really ask your students what they're doing with it and listen to their responses. And certainly we learned from the digital literacy research the importance of student voice, all of that student voice work that went on to really understand their perspective. So I would start there with asking students to talk openly without incriminating themselves, to talk openly with you about what they are using it for.  

So I have children who are at university, and I asked my children this, and one of them is using it. And I don't know if you know this, but in the UK there's a kind of housing crisis and no one could get any room and there's a website called SpareRoom.com. And you have to respond to requests and hope that you're one of the 50 people that are chosen. And he's created a little bit of code to respond to spareroom.com requests so that he can get some accommodation for next year. And it's about productivity. It's about being able to issue those requests really, really quickly and answer them all. So ask students what they're doing, because some of them are doing really interesting things and then set them activities relevant to your discipline where they compare the output from ChatGPT, for example, or other image creating tools, for example, AI based image creation tools, and evaluate them as if they were evaluating a piece of published work. So we ask students to do this all the time is to evaluate things against set criteria. So AI based tools are surprisingly good at poetry, at art generating art, if that is your discipline. You can ask them, you can create an answer. Literature and essays is the obvious one. Code, ask AI  to produce some code and get students to evaluate how good it is and to spot the errors in it.  

I had a good example from Medical Sciences the other week where they regularly apply quality evaluation frameworks to pieces of research, to published articles to say how trustworthy is this research? And AI can do that and then you can work as well to do it, to say, well, how good was the AI evaluative judgment about the quality of this research paper? So it can do really quite complex things. And then finally, I would say that work with students to think about how ChatGPT can improve its answers, because if you understand that prompt engineering, if you understand that conversation, then you understand how to use these tools well and wisely. And I saw Matthew in the chat has put in an AI framework and link, which was great. Thank you. Really interesting to see that. And in that there is a section how to prompt engineering. And then the website learn prompt, which I agree is really good for you, follow a course to teach you how to prompt, how to improve your prompts. And those are the kinds of activities that we need to help students to learn what to do.   

Senior Professor Sue Bennett: Well, in a way, we're only as good as the questions that we ask. And Michael, I'm going to allocate you the question that David Carlos has put in the Q&A. Hello, David, it's good to have you with us. About good strategies for integrating process and product and design and implementation.  

Professor Michael Henderson: Thanks Sue and thanks, David. Good to see you, and thank you for the gnarly question, I don't have an answer. I said to Sue that I'd answer this one, but I don't have an answer. It seems really, at the end of the day, we understand that the product is a poor proxy for learning like often we're trying to look into that product and make assumptions about what we think this person knows can do. And so it depends on the integrity of the line between the product and the learning goal. So we want to get to the process as much as possible. So how can we reveal the process? And in higher education, we're often really stuck because we don't see our students as frequently as we would like to be able to make judgments over time about their process.  

So how do we do this? I think in an AI world, I think an interesting strategy which I've seen being used sort of with regularity and with some success is variously have product, so you can ask AI to generate a product or you can be developing something collaboratively with students, and students then can individually or in groups then set about to defend, to contest, to extend, to utilise and to basically demonstrate that they have a sense of the quality of the thing that is being produced. So really in any way to be able to improve upon the language, to improve upon the idea, to be able to utilise something, there has to be a deeper understanding of the thing than the thing itself. So if we ask students to simply create an artifact, they will know this thing that has been created. But to actually make an effective judgment about the quality of it and to explain that, then it requires a bit of a deeper thinking than the artifact alone. And I think that is is where we need to find the interesting and creative approaches to be able to get students to go, well, what is the source material? And what are the interesting ways that we can get them to challenge and defend it, extend it, etc.. So sorry, David, it's a bit of an obvious answer and and I wish I had something a little bit more creative for you.  

Senior Professor Sue Bennett: Well, David might come back at you. Thanks Michael. Thomas, I'm going to pick up on some threads that I see in the Q&A, which are around things like regulation and and privacy. You know, obviously, Microsoft is a global company, so across a whole range of jurisdictions like, you know, where do you get a sense the thinking is at around maybe whether there's a need to rein in AI, whether and how privacy can be protected in terms of, you know, all the ways that it might be our privacy might be vulnerable to the reach of AI.  

Thomas King: Well, there's there's a lot to that, actually. If you want to unpack it all, I think I'd start by saying, you know, I can't I can't speak for either of the companies. But obviously there's already a swathe of privacy legislation. GDPR, California's got privacy legislation as do we and it is important for any company that offers services to be compliant with the the laws with which you intend to operate. And I think that's one of the approaches we have, is to obviously remain completely compliant to that. I think the next question is, are the laws adequate in terms of ensuring privacy?  

And I think that's a conversation for legislators, for society at large. I think certainly for academics to lead part of that conversation is to make sure that they are appropriate, because I think a lot of it hasn't necessarily been tested. If you think about  university. So I think there's there's lots of opportunity. There's also lots of challenges on the legislative and regulatory front around making sure that it is appropriate for where society wants to take advantage of this technology and where they feel like they need protections. So hope that's answered at least part of it, but let me know because there's a there's a bit to that one.  

Senior Professor Sue Bennett: Well, I think we could probably have a whole hour of discussion on that. I know we can't go into everything in depth and we've probably only got time now for one more Q&A. And I'm again going to try to get draw together a couple of things I see across the Q&A, and that's around inequality. Like how do we address inequalities in education through generative AI and at the same time, how then do we, I guess, provide or allow AI to be a support for a diverse range of different students? Rhona, I'm going to ask you if you've got anything that you'd like to share on that one.  

Professor Rhona Sharpe: Yeah, I mean, off the top of my head and I'm sure other people can bring suggestions to this as well. So I think it's really important that we consider the role of these tools in reducing inequalities as well as as I talked about at the beginning, that there might be inequalities embedded within them. And just a few examples, I think language English and academic English, if you think of all those times where someone has written feedback on students work that says things like write more academically. Yes, write in the style of the discipline and students are like 'I don't know what that means'. I don't know how to do that. You can ask ChatGPT to do that. You can say put this in a different style, put this in the style of something. And so it's really useful in helping students to learn how to write within the style of particular disciplines or genres.  

The second thing, and that was a question about disabled students. So there were already AI based tools like Grammarly. Spellcheck and Grammarly are both AI based tools which supports students to improve their written English, and I'm sure we will see many more of those kinds of things to support disabled students and disabled students and students with other diverse backgrounds and capabilities often talk about the the many more hours that they have to put in than other students to reach the same competencies. So any kind of academic productivity tools are going to be of support to students who are already putting in far more hours than other students. And then my third idea as we've been talking, is really about tutoring. So I know AI is not intelligent and its it's not thinking and it's not reasoning, but I have seen students use it effectively in a tutoring role. So where they have not understood a particular process or technique or topic, they can go back and forth in a way that they run out of class time or an academic's time to do that. And that will be helpful for students who to go through things more than once as well. So there are other ideas out there.  

Senior Professor Sue Bennett: Thanks Rhona, we are nearly at time, so I'm just going to move to the final part of our session today. And that's where I'm going to ask each of our panellists today to just offer a closing remark. So you might reflect on what we've discussed in our discussion, questions that are in the Q&A and comments. So I'm going to go to you first, Thomas, for a final remark.  

Thomas King: Yeah. So this space is going to continue to evolve very rapidly. I think when you see things like the likes of Microsoft Copilot in action, it will kind of challenge you. Hopefully in a in a positive way and there'll be a bunch of other tools from other other companies as well. But these changes are coming. So what do you need to do to prepare?  

One of my recommendations is you should seriously consider having an AI strategy for your institution that is as broad as possible. It's not just around assessment. It's not just around teaching and learning. It's around impact. It's around your partnerships. It's around the student experience you want to provide. It's about improving your university operations and administration. My call to action for all academics is if the biggest complaint that we've heard from so many in the community is that  you short of time, have you really sat down and thought how can you, your school, your discipline, your research center, how can you possibly take advantage of this to actually give you some of that time back to spend with your students, to spend contemplating how to solve research challenges, to free up time for your creative expertise to be used. And I think that the sector it's such a critical time for the sector to really show how valuable it is to society at large. And it's an amazing sector. And I think the sector will evolve with this and help guide and shape where this takes us to a degree. So I certainly look forward to working with a lot of you on the call to do that.  

Senior Professor Sue Bennett:  Thanks, Thomas. And I think that also speaks to one of the questions in the chat, which is, you know, what do we do about the governance that sits around change practices that we will need to bring in. So having a strategy that that sets that out and can guide implementation, certainly.  

Thomas King: Yeah. And apologies Sue, one more on that would be a practical example would be why we teach students the role of professional associations, for example. You know, what does it mean to be an engineer, a nurse, a doctor, a lawyer, an accountant? And I think these professions will evolve. And so industries, companies, professions will evolve. What they do in their job will evolve. But that's been true a lot of the time. Maybe it's going to evolve differently with this. You know, we'll wait and see. But there's a critical role for academic leadership to work with associations and with industry in general to help us navigate this. So yeah, so please lean in to it.  

 Senior Professor Sue Bennett: Thanks, Thomas. Rhona. Final remark from you.  

Professor Rhona Sharpe: I guess the precursor to developing an institutional strategy is talking about it. I know many institutions are putting together working groups or opportunities for discussion forums. So I think we need to talk about this. Talk to your colleagues. Over coffee. Over lunch. Talk to your computer scientists in your institution. Talk to your students about it. Spend the first 10 minutes of your next session with students talking to them about it. I know we are tired from the years that we have been through, but I don't think this is something that we can hide from.  

Senior Professor Sue Bennett: And that's a great point. I was reading an article just yesterday that was pointing out how little of the student voice we've heard so far. So that's certainly a place for us to turn our attention next, to seek to understand how students are already using it, how they're finding it as we work on that together. Thanks, Rhona. Michael, over to you.  

Professor Michael Henderson: Okay. I was going to talk about defending assessment from AI and getting back on my hobbyhorse, but I've changed my mind after what Thomas was talking about then. And I'm going to talk about defending assessment integrity, not student integrity, but what we do as educators and institutions. 

 A question that's often thrown at me is how can we use generative AI to reduce the burdens of educators, right? And the top items on their lists are, again, can we use it to help us with our marketing and our feedback? And I almost had a heart attack because out of every and any task that we have or duty and responsibility and honour and privilege as educators is the one thing of using our deep expertise of understanding quality and bringing that to bear to the student experience. And so in the assessment, when we're marking and when we're providing feedback, which is separate things entirely, okay, they're related, but they're separate practices. We need to be engaging in our sense of what is quality and how can this student improve. We can use AI to to act in corrective ways like the Grammarly example that Rhona was talking about in ways that can sort of reveal different ways of writing something with maybe spelling errors, things like that. But when it comes down to the essence of the quality, the depth of understanding, the disciplinary knowledge, the skills, those kind of things, then we are here for a particular reason. And so I'd be cautioning, as my last point is, about going for what seems to be low hanging fruit and inevitably sort  of working against ourselves in terms of our own integrity of education.  

Senior Professor Sue Bennett: Thanks, Michael. And I think that it's reminded us of something very important that certainly in the preparation for this that I heard repeated by many of our colleagues, which is not to lose sight of the fact that learning and indeed education are inherently social. And a lot of the satisfaction that we derive both from learning and teaching comes from that social nature.  

That's all we've got time for today. I want to thank each of our panellists, Thomas, Rhona and Michael, thank you for being here today for joining in this discussion. I also want to thank our audience, particularly for co-opting the Q&A in the way that they have this lots of wonderful sharing that's going on. And I agree. Let's talk to each other. Talk to the linguists. Teach us how to survive and thrive in an AI world, not ban it, which, you know, goes on beyond even just surviving in an AI world.  

I want to thank very much our Luminaries team who organised this event behind the scenes. And just a shout out to our UOW colleagues today. If you're joining us, the Vice-Chancellor is pleased to announce a new initiative for innovation in AI and assessment. This initiative will be in the form of a prize that recognises academic staff who embrace the use of generative AI that drives innovation and leads to improvement in teaching excellence, assessment practices, career readiness, and the student experience. The prize will be managed by our colleagues in Learning, Teaching and Curriculum, and the full details will be available in the coming weeks. So check out that Learning and Teaching Hub for more details.  

This event was recorded so that everyone who's registered will see receive a link to the recording via an email. As I said before, if there are questions that we haven't managed to get to, we will endeavor to put something together and use that email list to circulate that. Thank you again for joining us and if you've enjoyed this session, please check our website for other events in the Luminaries series. So thank you. And that's a wrap, everybody.  

Katrina Green: Good afternoon, everyone. I'm Associate Professor Katrina Green, a neuro-pharmacologist in the School of Medical, Indigenous and Health Sciences at the University of Wollongong, and I'm also Deputy Director, Community Outreach of Molecular Horizons. So it's a pleasure to welcome each and every one of you here today.  

Luminaries brings together leading researchers, industry experts and thought leaders for one hour conversation every fortnight. We will discover how research and collaboration at the University of Wollongong is tackling global challenges. And today we are hearing from a group of exceptional colleagues as they discuss the biology and treatment of depression. But before I start, I'd like to acknowledge Country.  

So on behalf of the university I would like to acknowledge that country for Aboriginal peoples is an interconnected set of ancient and sophisticated relationships. The University of Wollongong spreads across many interrelated Aboriginal countries that are bound by this sacred landscape, an intimate relationship with that landscape since creation. From Sydney to the Southern Highlands to the south coast, from fresh water to bitter water to salt, from city to urban to rural. The University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space that has kept alive the relationships between all living things. The university acknowledges the devastating impact of colonisation on our campuses footprint and commit ourselves to truth telling, healing and education. Thank you.  

So in Australia, one in six people are currently experiencing depression, anxiety or both, with women reporting higher rates of depression or feelings of depression and anxiety than men. And major life transitions such as pregnancy and motherhood can impact on women's mental health and wellbeing. So this webinar explores the biological changes in the brains of those with mental illness and current research that seeks to understand sex differences in the biology. New research focuses on how various approaches to the treatment of maternal depression alter maternal behavior and the maternal brain. And today, we welcome leading and early career researchers to discuss their current work in depression research.  

So if you have any concerns about your own or others mental health, please talk to your doctor or call Lifeline to seek advice using the number on your screen.  

So I'd like to introduce Professor Kelly Newell. Kelly leads a research team that focuses on the neurobiology and treatment of mental illness, including depression and schizophrenia. She utilises postmortem human brain tissues and rodent models to uncover biological changes in the brains of those with mental illness to guide research into more targeted treatments. She has research interests in the biology of antenatal depression and the impacts of antenatal depression and its treatment on the maternal brain and offspring outcomes.  

We also have Sue Thomas who is an Associate Professor of Mental Health and Behavioral Sciences at the Graduate School of Medicine. She leads the Mood Food and Biomarkers Research Program, which investigates how depression is related to physical health changes, including hormones, appetite, weight gain and heart health. She's also a practicing clinical psychologist.  

Samara Brown has just completed her PhD, where she utilised human brain samples to explore neurobiological changes that occur in depression. And Samara continues this work post PhD, while also examining the neurobiology and novel treatments for schizophrenia.  

And we also have Noor Jarbou who is a behavioral and molecular neuroscientist. Noor has also just completed her PhD, where she explored the impact of antidepressant use and exercise during pregnancy on the maternal brain and on depressive and anxiety related measures. So if I can ask you first, Kelly, how big is the problem of depression and what's your team doing to tackle it?  

Kelly Newell: Yeah, thank you, Katrina. We all know someone with depression. The incidence of depression is high and it's rising. We've got treatments for depression which work for some, but not all. There are a lot of people that aren't experiencing relief from current treatments for depression. So really, to discover more effective treatments, we really need to understand the biology of what is going on in people with depression so that we can design better and more targeted treatments.  

So one of the ways our research group is tackling that is really to look at the brain itself from those that have experienced depression and understand on a molecular level what has changed or what is different in the brains of those with depression, so that we can use that to design better drugs or better targets for the treatment of depression.  

Samara has spent the last four years dedicated her life to answering this question. She has been investigating a specific pathway in the brain that not much has been known about this pathway in depression. And her research really could help identify new treatment targets or new treatment targets for specific groups of people with depression. She's found some interesting findings that are specific to females with depression, which really could provide important information regarding treatments moving forward. Thanks, Katrina.  

Katrina: We're now going to hear from Samara, and I'd encourage members of the audience to submit their own questions using the Q&A function. And we'll try and get to as many questions as possible. Thanks, Samara.  

Samara Brown: Thanks, Katrina. I'll just bring up my slides. Hi everyone, my name is Samara Brown, and over the the last four years I've been completing my stay here at the University of Wollongong. So the focus of my PhD has been investigating the molecular mechanisms underlying major depressive disorder. And so I'll be taking you through some of the key findings of my PhD here today.  

So major depression is a severe psychiatric disorder and it affects over 260 million people worldwide. And so largely, we don't know what's happening in the brain in depression. So as a result, the underlying neurobiology is unknown. It is thought, however, that it is a complex interaction of molecular changes, the environment, genetics and development that are contributing to the development of depression. So the treatment of depression is largely inadequate.  

Only a third of people that experience depression are going to have the ideal response to the first treatment that they try. Another third will take two or more treatments before they have any benefit, and the final third are considered treatment resistant. So those that do respond to antidepressant treatment will have to wait up to 6 to 8 weeks before some of them will actually see a therapeutic effect. And so this is largely because we don't know what it is we're trying to treat in the brain. And so I've highlighted three clear groups here. And based on that, we suggest that there's actually differences in the neurobiology between these three groups. If we see medication working in some but not all individuals with depression.  

In addition, there's a lot of sex differences in depression. However, it's largely unconsidered in molecular research. So females are disproportionately represented in the depression population and on average have doubled the prevalence of depression in comparison to males. In addition, the symptom presentation is generally more severe in females, so they show prolonged or recurrent depression more often. There's a younger onset of age and in addition, there's a lower quality of life. An important identification here as well is that the antidepressant drug response between males and females is different. And so even though we know all of these sex differences exist in major depression and it's been known for over half a century, a lot of molecular studies are not designed to investigate any sex specific changes. And so my research really wanted to focus in on this.  

So for my research, I use human brain tissue and it's a really important tool for our depression research because at its core, depression is a mental disorder. And so we want to know what is happening in the brain. So it's significantly underutilised. A lot of clinical research using blood samples because it's a lot easier to access. And so we're just trying to marry up some of that information by focusing on brain changes. So I'm able to use a piece of brain tissue about the size of a green pea. And from that we can learn a lot about the molecular pathways that are in the brain and hopefully identify what could be altered in the brains of those that had depression during their life. It's hoped that by doing this, we'll be better informed to understand the disorder and also help identify subgroups of the disorder. And so combined, this will help us to identify novel treatment targets that are hopefully more effective than those that we have at present.  

So my PhD., I focused in on a pathway called the kynurenine pathway. And this is a more novel target pathway in depression. It's the major tryptophan metabolism route in the brain. And so tryptophan is one of the essential amino acids that we get from the diet. And the really exciting thing about this pathway is it converges a lot of the existing hypotheses that we had about depression dysfunction in the brain. So in the brain, this pathway is activated by both stress and inflammation and then dependent on cell type. So in the brain, we have these two brain cells, we've got our microglia, and our astrocytes. Depending on that cell type, we get the production of different metabolites. So in microglia will get the production of clean quinolenic acid. It's going to go around activating receptors in the brain, whereas in astrocytes we get what's called kynurenic acid. It does the opposite. It's going to block those receptors.  

And so there have been some previous studies in depression on the kynurenine pathway, in blood samples from people with depression. And what they've found is significant reductions in this blocking metabolite. And so what this meant is that quinolenic acid was pretty much free to flow around activating receptors without any competition. And what this would lead to is increases in excitotoxicity if this was present in the brain. So my research aimed to check if this was the case in the brain.  

So I have obtained brain tissue from individuals with a history of depression, and we also get brain tissue from non psychiatric controls. The region I focused on is called the anterior cingulate cortex. So this is a key emotional regulation site in the brain and it's shown to be altered in depression previously. After we gathered our brain tissue, we were then able to examine the gene expression and metabolites of the kynurenine pathway. So what I've got on the left here is an example of a of a non psychiatric control synapes in the brain. So this is where we're getting our signaling and messages sent around the brain. So ideally what we want to see is a balance between these two metabolites. So we want to see some activation but also some inhibition. This means that we can control and have a healthy brain signaling. So after investigating this pathway, I first looked at inflammation in the brain because it can activate the kynerenine pathway. And really interestingly, we found that there was increases in these inflammatory markers in the brains of people that had depression, and this was irrespective of sex. So both our males and females with depression had significant increases in inflammation. And so what we thought that might lead to is an increase in our kynurenine pathway.  

When we then went on to investigate the kynerenine pathway, we did find some changes here. So first we looked at gene expression of the enzymes. So these are the things that are going to generate the metabolites. And what we saw is that this enzyme called KAT 2 was increased in depression. So this enzyme is going to increase the amount of our inhibitor metabolite kynurenic acid. And so we predicted that we would then also see an increase in kynurenic acid opposite to what was previously reported in the blood. And so that would mean that we'd have increased potential to block excitation in the brain. And so this can be considered neuroprotective, which was kind of opposite to what we had expected. When we did some further subgroup analysis based on the cause of death, we found that it was actually only depression subjects that did not die by suicide that showed this increase. And so this could possibly mean that we have increased neuroprotection in those that did not die by suicide.  

The next step was then to actually measure how much of that metabolite was this enzyme making. And interestingly, what we found was that those that had died by suicide had a significant reduction in kynurenic acid. So they had a lot lower potential to block the receptors. And that meant that our depression subjects that did not die by suicide may have had neuroprotection from that increased enzyme expression. The next step was to consider those sex specific changes. And really interestingly, we found a specific focus on females with major depression rather than males. And so similar to our suicide findings, we found that females with depression had significantly lower levels of that inhibitor metabolite kynurenic acid when we compared it back to female controls, when we then compared the ratio of activation and inhibition metabolites, we saw that females again had a significant decrease. And what we proposed is that the kynurenine pathway dysfunction that we're seeing here may be specific just to females. And the implication of this is that we may see increased excitatory excitatory signaling in the cingulate cortex, just in females with depression. And so why this is important is that if that excitation is above healthy levels, we can actually see damage caused to the brain.  

And so overall, if we wrap up these findings, what we saw is that the kynurenine pathway changes were specific to certain groups of depression. And moving forward, we want to know can we target the kynurenine pathway in females with depression? And would these drugs also be beneficial for suicidality? So we need more research conducted in female populations and also female preclinical models so that we can see a greater research effort into trialing these kynurenine pathway drugs specific to these groups. And so just lastly, I'd like to thank the wonderful team I worked with on this project, and thank you all for listening today.  

Katrina: Fantastic. Thanks, Samara. I have a question for you. The really interesting findings and I was just wondering if there's any kynurenine based therapeutics that have been trialled in depression.  

Samara: Yeah. So there's some really exciting research starting to happen. So there is a drug that's aimed at boosting kynerenic acid levels in the brain. But one of the major caveats of this is it's actually only being trialed pre-clinically in male rodents. And so we're not actually sure what the impacts would be in a female kind of model. And based on our research, we really think that's where we need to be testing these drugs to see what kind of benefit they could have. So it's kind of a watch this space for that drug.  

Katrina: Okay, great. It's good to know that new things are on the horizon. So a question for Kelly, we know that depressive symptoms are common to multiple disorders, including major depressive disorder, bipolar disorder, and even schizophrenia. Do you expect to see similar biological changes that you've seen here across the other disorders?  

Kelly: Yeah. Thanks, Katrina. That's a really good question. And, you know, I think that's part of the challenge sometimes of identifying the biology of these disorders, because there is overlap in the biology and in the treatments even for these disorders. So in Samara's work she does have the work that she's presented is on unipolar depression, but she does have some preliminary data from subjects with bipolar depression suggesting slightly different pathology.  

One of the projects we're moving forward with now is a project on schizophrenia to see exactly that. How is the biology different between, say, depression and schizophrenia? And there are certain elements that can overlap. For example, the evidence that Samara has found of increased inflammation in the brain. There's also a lot of evidence coming through that there's higher inflammation in the brain in schizophrenia as well. So I think there's some elements where the biology overlaps and some elements where it is quite different and something that we're looking at moving forward.  

Katrina: Yeah. Interesting. We had a question from the audience perhaps Samara could answer about whether there are differences in collection time of tissue between time of death and freezing tissue between suicide and non suicide patients.  

Samara: No worries, so this is data that we get given from the brain banks that we get the tissue from, and we make the best effort to make sure our groups are matched. So there were no significant differences between it's called post mortem interval, so from time of death until about brain tissue is collected and frozen. So we were able to check for that in our analysis, and there was no differences across the groups.  

Katrina: Great. So I have a question for Sue. So as a clinical researcher, how important do you think it is to focus on understanding if there are differences based on sex in depression?  

Sue Thomas: It's very important because in the clinic we see that males and females often present with different types of symptoms in MDD, and they can be a very different symptom profile for someone who still has the same diagnosis. And it's it's crucial really to look at the clusters of symptoms and how they relate to the different biological pathways. So we'll be touching a little bit on that in my slides in a minute. So perhaps I can put up my slide when we're ready.  

Katrina: Okay, great. Just before we go across to that, Kelly, I was just wondering where you think you would take the research from here.  

Kelly: Yeah. Thank you. Obviously, the aim of doing this research is so that we can transition or translate it to the clinic. Where we need to take this research from here at the first instance is really to get an understanding of whether these changes that Samara has identified are happening more broadly in other brain regions that are implicated in depression. That's really, I think, the first thing we need to understand. But then moving forward, exactly as Samara has said, going back to trialing those drugs that target this pathway. It's really exciting these drugs are in development and happening, but trialing them in both male and female models before translating them to the clinic I think is absolutely essential.  

Katrina: Yeah, I agree. Fantastic. All right, we will now hear from Sue who will be discussing her clinical depression study. Thanks Sue.   

Sue: Well, just briefly talk a little bit about the Mood, food and biomarkers research program happening here at the University of Wollongong. So just leading in nicely from Samara's findings of the sex differences at the biological level, when we go to diagnose major depressive disorder in the clinic, the person first of all needs to have an enduring low mood or a loss of interest in just about everything. And then they can have a pick and mix of at least four other symptoms from this lower list here. And these symptoms can also go many of them in different directions. So you can have an increase or decrease in appetite, an increase or a decrease in sleep or in activity levels. So you can see you can imagine this quite great variability possible. Someone calculated that it's possible to have around a thousand different symptom presentations for a diagnosis of MDD. And also it's possible for two people with MDD to have absolutely no overlapping symptoms. So we have to consider the symptom level, not just the diagnosis in our research.  

It shows the importance of the of the biology as well. So people with depression are at greater risk of chronic disease. And this is a focus of of the research program that I'm talking about. We know as well that there are sex differences in some particular symptoms. So females are far more likely to experience fatigue, increased appetite and hypersomnia. So definitely at the end of the spectrum of sleeping more and eating more. We know that stress triggers neuroendocrine responses in the body. And the best researched of these, of course, is cortisol. But there's also a cascade of involvement of other hormones and blood biomarkers that we're focusing on about which less is known.  

We're interested to know how are these related to specific symptom profiles with the aim of guiding more precise treatments in future. So the Mood, Food and Biomarkers research program, it looks at the whole person and we invite people into the University of Wollongong for one session and we take a very thorough assessment of all of their mental health symptoms, all of their depressive symptoms. And we look at the their physical health, their heart health and their body measurements, etc. We assess their lifestyle and their diet and the nutritional intake, the eating habits, hunger levels, exercise and other lifestyle factors. We take blood samples and look at the blood biomarkers and look at a number of hormones related to stress, appetite, mood metabolism, sex hormones, inflammatory markers, neurotrophic factors, and some other ones as well, including glutamate, which is which is relevant to the previous presentation. And I guess our overarching question is why are people with depression at greater risk of chronic disease, and particularly people with different clusters might have different risks? We have a whole team of multi-disciplinary researchers working in this space, and some of our key findings just briefly are that looking at the increase in appetite and weight, which is so frequently seen in the female participants with depression, it's closely linked to the hormone leptin. Now leptin is normally a satiety hormone that sends a signal to the brain to stop eating because you've got enough nutrition and you've got enough body fat. But in this subgroup of women with major depressive disorder, the signal is no longer working and they're not sensitive to the signals. So they have no cessation in appetite. They're constantly hungry and gaining weight. This is one pathway to chronic disease for this subgroup and it is linked to potential treatments in future. We've also managed to trace particular patterns of negative thinking, such as suicidality to cortisol levels in the blood, social support to oxytocin levels in the blood. And we've found significant disturbances in several other biomarkers in MDD. So we have people working in this space. So just very briefly, if you are interested, we are recruiting for people both with depression and without depression. Males and females, if you're interested in participating, there's a contact for Stephanie Roemer and she can give you some more information.  

Katrina: Right. Thanks Sue. Are there any questions from the audience for Sue? If there are just pop them in the chat. In the meantime, the fact that depression is more common in women, it raises the question about risk of depression during pregnancy. And before we hear from Noor, our next presenter, about what she is doing in this space, Kelly, would you like to provide an overview of the research that's happening?  

Kelly: Yes, sure. Thank you, Katrina. Yeah, we know depression is more common in women. It's common in the 20 to 40 year age range, which is a common time for falling pregnant. There has been a growing focus on postnatal depression and the risks and awareness and treatments of postnatal depression, but there really has been a lack of awareness and understanding of depression during pregnancy, which we term antenatal depression and the treatment for antenatal depression, which is what Noor is going to touch on. So as part of our research program in this space, we've really been looking at pharmacological so drug based treatments but also non-pharmacological pathways to treatment, such as exercise, and how effective they are both on the mum but also on the developing offspring. And I think in the past or up to this point, there has been a lot of focus on the offspring and less actually in the research space and less research on actually what is happening to maternal behavior and to the maternal brain with these various different treatment approaches, which obviously is key and very important to make sure mothers are treated appropriately and in the best possible way based on evidence. And that's where Noor's research comes in and what she's been focusing on for the past four years or so.  

Katrina: Fantastic. Thanks, Kelly. So we'll now hear from Noor and the research that she's been doing. Thanks, Noor.  

Noor: Thanks, Katrina. Good afternoon. So there are various theories used to describe the patient during pregnancy, post-pregnancy periods and clinical depression refers to depression that is experienced during pregnancy. It affects up to one in ten women in Australia. And this number can be even higher in other countries.  

Postnatal depression develops between one month and up to one year after birth. It affects up to one in six women. The term perinatal depression covers the whole period from conception to 12 months post birth. Antenatal depression is one of the strongest risk factors for the development of postnatal depression, and if unmanaged it can be associated with increased risk of weakened mother child bonds and a range of other risk factors to both Mums and babies. Therefore, it's important that it is treated.  

Other psychotherapy drugs known as selective serotonin reuptake inhibitors, such as sertraline, are the most common treatments during pregnancy. While this works well for some women, others do not see relief from the symptoms and some women with seek other options. That's why research is needed to ensure we have that evidence base for treatments during pregnancy and beyond.  

During my doctoral thesis, I have been exploring selective serotonin reuptake inhibitors and exercise during pregnancy impact, depressive and unsafe behaviors in mums, and also the effects on the maternal brain. I'm only going to focus on the exercise side of my research. So there's a growing evidence saying that exercise has the ability to elevate symptoms of mild to moderate depression in the general non-pregnant population. And also clinical studies showed that exercise in pregnancy also has beneficial effects on the general health and well-being of the mother and baby.  

Moreover, the WHO recommends that individuals, including pregnant people, engage in 150 minutes of moderate intensity or 75 minutes of vigorous intensity exercise per week or a combination of both. However, there is very limited research into the effects of exercise during pregnancy on depression, anxiety and associated symptoms. So I investigated the literature to see what clinical research has been done exploring this exact question of what are the benefits of exercise and pregnancy on depressive and anxiety symptoms. In what we published last year, we found that there have been 27 studies that have examined this. However, only five studies had actually recruited women with perinatal depression. And in these studies, the only exercise intervention that was used was a yoga intervention.  

Despite that, of the five studies, four did show that compared to the baseline, there was an improvement in both depressive and anxiety symptoms after the yoga intervention. However, in two studies of those five studies, the control group, the non-yoga group, showed an improvement as well. Well, this makes it really difficult form firm conclusions, and highlights that we need more research in this area. For the rest of the 22 articles that recruited women with no depression, they used a range of exercise protocol, as you can see here, beyond yoga. 18 of those 22 articles showed that exercise interventions in pregnancy can improve depressive and or anxiety symptoms without that perinatal, prenatal or postnatal. And overall, while it's promising, that just has not been enough research done to understand the benefits of exercise and pregnancy extending to depression. So I ask myself questions. Can higher intensity exercise during pregnancy improve depressive or and anxiety symptoms? The second question, What effect does it have on maternal brain?  

I designed a rodent study where I used a rodent model of depression and provided them with access to running wheel through their pregnancy. I had two control groups to compare to, one depression rodent model with no access to running wheel and a non-depression control. At about five weeks postnatal, we ran a series of behavioral lists to examine aspects related to depression, anxiety and cognition. We also conducted molecular examination of maternal brain to determine if the exercise intervention had the ability to induce long lasting brain changes. We examined anxiety-like behavior in the mums using two different methods to ensure robustness of our findings. The first was on the open test,  as you can see, it's a fairly simple test where we place the rodent in that square box and we measured the time spent in the corners of the box, as you can see here, and which are deemed safe as represents higher levels of anxiety. And how much time spent in the center of the box, which represents less anxiety like behavior. As you can see here, at five weeks, the exercise group showed an increased time spent in the center of the open space box, indicating a reduction in anxiety-like behavior. We then followed this up with elevated plus maze. As you can see in this test, we have an elevated plus maze up off the floor, as you can see, two arms have walls and the opposite two arms don't have the walls. And when rats spend more time on the safety closed arms, it represents higher levels of anxiety like behavior. And when they spend more time in the open arms, it represents a reduction in anxiety-like behavior. As you can see here, the exercise group after five weeks of exercise intervention spend more time in the open arms and less time in the closed arms. And again, this reinforces our earlier finding that exercise and pregnancy was associated with reduced anxiety like behavior.  

We followed this with an examination of the gene expression in the brain to determine if the exercise intervention could induce long lasting brain changes that might be associated with the behavioral changes we were seeing. I first focused on images related to DNA methylation, which regulates the gene expression, as you can see here, the chromosome and once it's unpaired you can see here the  DNA that contains the genetic materials. And here are the methyl groups here. And when it is added to the DNA strand, it can influence the gene expression. As you can see here, that the exercise group increased the enzyme called DMNT30 that facilitates that DNA cortex only and this suggesting cortical changes in this region. What are the implications of our findings? First, these findings suggest that in our rodent model of relevance to depression, that voluntary exercise, or running, reduces postnatal images of anxiety in rat mums and that could be related to long term changes in gene expression in the cortex. This provides a foundation to translate these findings to see if they apply in a clinical population. And finally, I would like to thank all of the people who contributed to the success of the animal study.  

Katrina: Great work Noor. So I have a question for Kelly about the long term benefits. The long term benefits of exercise in this regard are very exciting, how do you see this translating to humans?  

Kelly: Thanks, Katrina, and thanks Noor. Definitely some very interesting findings. And I guess there's a few points to make in that regard. The first thing being we don't have a comparator here to standard treatment. So the results don't necessarily say that this is more superior to pharmacological treatment or psychotherapy. So we need to keep that in mind when viewing these findings. But I think that is part of the next step in this research. We need to have an idea. Is this how the improvements that we're seeing in a rodent model, keeping in mind that this is early stages, you know, how does that compare to treatment with SSRI's? How does that compare to other treatments for depression? You know, for any of us that have been pregnant, talk about exercise in pregnancy, you know, sometimes that is the last thing that we feel like doing when we are pregnant.  

So some of the work that we have done following this up really is starting with surveying women and women with a mental illness to get their perspectives and their experience of exercise in pregnancy. What are the barriers to this? We know that at the moment, based on some of Noor's results that she hasn't presented today, that women with a mental illness during pregnancy are exercising less than those women without. And there are a range of factors that would explain that. But really understanding those those barriers and those perceptions, you know, I think women have different perceptions of safety, of exercise in pregnancy. So understanding that and moving forward with that is is really important as well.  

Katrina: Thanks, Kelly. I have some questions from the audience, if I may. So one is for Sue. Do you have any biomarker data on omega three status? As you know, omega-3 supplementation has improved depression scores in people with depression.  

Sue: Yes, we do, actually. We have collected and analysed data on 120 people looking at omega-3 status, and half of those were people with a diagnosis of MDD and half were sort of healthy controls. And we thought we might find some deficits in the group with the depression. But what we found actually was a bit more depressing than that actually. We found that in both groups they both had very low levels of omega three circulating and they fell within a deficit range, which would put them at risk of both mental health and heart, cardiovascular problems down the track. And given this is a seaside place where we collected the data, it was it was quite a surprise. But it suggests perhaps there are dietary, you know, things that are suboptimal in people who are living locally and, you know, around the university. And one wing of our research is now looking in a lot of detail at the dietary intake. So we hope to be able to pinpoint why this is. But I think it's a really good point that supplements may be worth considering. And definitely we should look at people's dietary intake. We're finding just lower quality intake in the people with depression. But omega three status was poor across the board.  

Katrina: Great. So I just have another question from the audience. So just about the biology of treatment resistance in depression. And do we know much about some of those driving factors of treatment resistance? Open to anyone on the panel.  

Kelly: Yeah, I think that's a really challenging question, and I think that's one of the big aims of the research, especially in terms of defining our subgroups rather than just looking at depression as one homogeneous disorder where everyone's got the same biology. Really looking at the molecular changes and letting the data define subgroups for us so that we can determine what is different about those with treatment resistant depression. We know that antidepressant drugs, the majority of antidepressant drugs target the serotonin system in the brain. Definitely those people that aren't responding to those drugs, you know, we would predict that there would be fewer serotonergic disruptions in those people. So really finding out what those disruptions are. Ketamine is a drug that has been of interest for the treatment of depression of late. There's a lot of research happening in that space, and it targets the glutamate system in the brain. And it's showing a really promising and rapid effects for those people with treatment resistant depression. So it does suggest that in that population, the glutamatergic system in the brain, which is another chemical pathway in the brain, really might be the driving or one of the driving biological changes in that group.  

Katrina: Thanks, Kelly. So there's also a question about and I think this might be to do with your literature review Noor, and whether you noticed, whether any of the pregnant mothers were known to have depressive or anxiety feelings prior to being pregnant, is that sort of data captured in the things that you looked at for yourself for your review?  

Noor: Well, actually, most of the articles we had didn't go through previous experience. So our aim was to look for the studies that had exercise during pregnancy and did assessment on the person for anxiety like symptoms, but nothing to do with previous depression before getting pregnant.  

Katrina: Yes, thank you Noor. So another audience question is around whether studies look at how social determinants such as poverty or violence might also impact depression in the brain. Would someone would like to answer that question? 

Samara: In terms of the biological studies that I've been conducting, unfortunately, we just aren't able to capture that information. We're kind of limited by the information that the brain banks provide us. And so that happens because a lot of our data is collected postmortem and so relies on a lot of surveys with family and the psychologist that that person may have been seeing. So while it is super important and possibly Sue might be able to attest to this more in the clinical space, I think that is considered.  

Sue: Yeah. Shall I come in now?  

Katrina: Thanks Sue. 

Sue: Yes. This area of research is actually becoming turbocharged at the moment. And there's a lot of people looking at childhood adversity and how that sort of has a knock on effect biologically down the track. So females are more likely to experience childhood adversity, you know, in the form of some sort of violence or abuse. And it looks like the earlier activation of anxiety and depression and just the chronicity of it leads to some of the longer term problems that we see in the greater impact in females. So there's a lot of research that I'm noticing in this field at the moment. It is really exploding and I think we'll see a lot of things coming out. We sort of look at the chronicity of the depressive episodes, but it's not our main focus. We've got a lot of things to focus on.  

Katrina: Thanks, Sue. There's another question in the Q&A about measuring protein levels. I think this might have been about Noor's rodent study. Have you looked at changes in the brain Norr of  these rodents?  

Noor:  Yeah, the change that the biology or the gene expression.  

Katrina: Gene or protein expression.  

Noor: Gene. More like I was focusing on the DNA methylation process which is facilitated by certain enzymes and I presented one of those enzymes has been influenced by that exercise on pregnant rats.   

Kelly: If I could just add to that, Katrina, thank you Noor. One of the other elements that we're looking at in that regard is neurogenesis or the birth of new neurons in the brain. So we know in pregnancy that there is a reduction in gray matter. So a reduction in brain tissue and a reduction in neuronal number in healthy pregnancy. You know, a lot of people may experience cognitive loss where if I put my keys, that kind of thing, and that is put down to this normal process of reduction in neurogenesis in the brain. And then it's thought that in depression that that is compounded even more. We know in people in the general population, one of the ways that exercise and anti-depressants work is by increasing neurogenesis in the brain. So one of the things that we're looking at the moment as a follow up to what Noor has found is counting neuronal numbers and looking at measures of neurogenesis to see if that may be the mechanism of how exercise is inducing these long lasting changes in the brain. So we're just this close to getting that data and those findings, so hopefully we can get that soon.  

Katrina: Fantastic, thanks Kelly. So in the last few minutes, I was just wondering if you can elaborate on further research and funding opportunities that may present after these early career research projects.  

Kelly: Yeah, I'll touch on that one if you like katrina. This is a challenging question and is a really challenging area for medical research generally. At the moment, the research is moving forward. As you indicated at the start, Samara is continuing on a postdoctoral position here to continue the research and expand it more broadly into schizophrenia, thanks to some research funding we have in that space. But there's really limited funding in medical research and research into mental illnesses and depression at the biological level. At the moment, the research into antenatal depression that we're doing is limited by research funding. And so really at the moment we're trying to come up with ways to move that research forward. But it is definitely a challenging space right now. Sue, did you have anything else you wanted to add in that regard?  

Katrina: All right. Thank you, Kelly. There aren't any more questions from the audience. I suppose perhaps just a final comment from the panel about how this work supports the broader work that's happening within Molecular Horizons at UOW in terms of clinical research.  

Kelly: Yeah, I can touch on that, Katrina. And there is a large amount of research happening in Molecular Horizons and university more broadly in terms of molecular pathways in disease, diseases of the brain, cancer, a whole range of disorders. And I think the group that we have here and having Sue and ourselves talk about the clinical and the preclinical research shows some of the diversity that is happening. We have a range of other research, is doing a lot of clinical research, a lot of research at the molecular level for neurodegenerative disorders, neuropsychiatric disorders, so depression, schizophrenia, bipolar disorder. There really is a lot happening in that space and it really does to move it forward really does require this collaborative approach of clinical and preclinical research.  

Katrina: Fantastic. Thanks, Kelly. All right. Well, a big thank you to Noor, Samara, Sue and Kelly, for joining us this afternoon. And thank you also to our audience. And we hope that you've enjoyed this discussion. So this event was recorded so everyone who's registered will receive a link to the recording via email. Thank you all again and good evening.  

David Currow: Good afternoon. I'm David Currow, Deputy Vice Chancellor and Vice President of Research and Sustainable Futures at the University of Wollongong. It's a pleasure to welcome each and every one of you here today to our Luminaries webinar series. Luminaries brings together leading University of Wollongong researchers, industry experts and thought leaders for a one hour conversation every fortnight. We will discover how research and collaboration at the University of Wollongong is tackling global challenges.

Today we're hearing from a group of exceptional researchers as they discuss the role of data and artificial intelligence in Australian healthcare. But before we start, I would like to acknowledge Country.

On behalf of the university,  I would like to acknowledge that Country for Aboriginal peoples is an interconnected set of ancient and sophisticated relationships. The University of Wollongong spreads across many interrelated Aboriginal countries that are bound by the sacred landscape and intimate relationship with that landscape. Since creation from Sydney to the Southern Highlands to the South Coast, from fresh water to bitter water to salt, from city to urban to rural, the University of Wollongong acknowledges the custodianship of the Aboriginal peoples of this place and space that has kept alive the relationships between all living things. The university acknowledges the devastating impact of colonisation on our campuses, footprint and commit ourselves to truth telling, healing and education.

Data are now at the center of human lives. Artificial intelligence built on healthcare data promises a new and transformative kind of health technology. However, this raises big questions. The promised benefits of big data and artificial intelligence be reached and then delivered. And if they are, what are the ethical and social implications of sharing and using big data and employing artificial intelligence based technologies in health decision making? It's my pleasure to introduce you to our researchers today.

Professor Lisa Smithers is an epidemiologist whose research mostly encompasses perinatal and pediatric epidemiology. Much of Lisa's research involves the use of population based datasets and data from large cohort studies. However, she also conducts clinical trials in hospital and community settings. Lisa has a special interest in the application of methods to improve causal inference from observational studies.

Professor Alberto Nettel- Aguirre has developed his career working collaboratively in health and medical research and has worked extensively as a biostatistician in a range of projects, namely around pediatric nephrology, neonatology and injury prevention. His expertise and interests cover the correct application of biostatistics and the implementation of statistical learning methods in health and social research. Alberto is one of the University of Wollongong's representatives at the Australian Data Science Network and leads the Center for Health and Social Analytics within the National Institute for Applied Statistics Research Australia at the University of Wollongong.

Professor Stacy Carter is the founding director of the Australian Center for Health Engagement, Evidence and Values in the School of Health and Society at the University of Wollongong. Her training is also in public health and her expertise is in applied ethics and social research methods. Stacy's research program addresses the ethical and social dimensions of four key challenges for health systems using artificial intelligence, detecting disease in populations and individuals, reducing harm and waste, and encouraging vaccination.

Dr. Yves Saint James Aquino is a philosopher and physician with expertise in philosophy and ethics in health care. He is a post-doctoral researcher, research fellow at the Australian Center for Health Engagement, Evidence and Values. His research projects include the ethics of artificial intelligence, the ethics of cosmetic surgery, body image research and social justice in public health.

Before we begin, I encourage everyone online today to submit their own questions using the Q&A function. We will try to get through as many questions as possible.

However, to kick things off, I'd like to ask the panel about data and artificial intelligence in Australian healthcare. Where are we today and where could we be in the next ten years? I'd like to kick off with some thoughts.

Alberto Nettel-Aguirre: Well, everybody knows I never keep my mouth shut, so I'll just start. Why not? You know, I think it is very important. There's several things that we need to be thinking of. What we understand by what people think is a AI in health care. You know, things like dictation or voice recognition on medical note is already AI, CAT scans all of these things that we use, the tools, are they AI when it comes to using it as a tool for diagnosis or for actual treatment? I think that's the big difference on what the expectations of people are. So where are we? I think we're still at a baby steps in a way. Where could we be in ten years? It will depend a lot on what people decide to do regarding data, data quality gaps, collection, etc.. That's my first go at it.

David: Fantastic. Thank you Alberto.

Stacy Carter: It's interesting you say that. I love it when when I think about this, I actually think back to five or ten years ago. And for those of us who've been thinking about artificial intelligence and healthcare for a while, there was a lot of hubris around five or ten years ago.

You know, there were there were big tech companies saying that they were going to build learning health systems that could absorb all of the data from a hospital and could do almost everything. There were leading developers who were saying radiologists would be extinct in five years and and we are training them now. But there are these huge claims being made at that time. I feel like that's become a lot more measured now, and I feel like that's really shifted just in the last couple of years, actually. But I think there's still quite a lot of excitement about the promise of artificial intelligence built on data. You know, that you can't have artificial intelligence without data that's so interconnected. And I'm sure we'll come to that more as we go.

But there's a pattern, I guess, that's connected to the difference between the hubristic claims a decade ago and what's happening now that, you know, you see those headlines all the time 'AI beats panel of seven radiologists', you know, similar kind of shape of headline. And that's often based on research that's done by the manufacturers of the systems, research that's based on really quite artificial datasets, you know, synthetic datasets that have been essentially changed to make it easier for the AI to learn to do the thing that it's meant to be doing. And then when you get those AI out into the wild, right out into the real world, and when you have really good quality health and medical research done on their performance, they often don't perform as well as they did in those quite artificial situations. And I think what's changed recently is that the clinical and public health community has really come to terms with that problem. And they've really started to talk about, okay, what do the standards need to be for AI research in health? And maybe they need to be higher in health than they are in some other places. How can we evaluate real world performance? How can we make sure that these algorithms actually are fair, not just that they work, but that they don't treat some people unfairly relative to other people? How can we make sure that patients and clinicians and the public are involved in setting the agenda and in development?

So I feel like we're at quite an exciting point. But like Alberto said, we actually really have to make some commitments at this point to make sure that this technology goes the way that that we want it to. And Yves has been been talking with quite a lot of experts about this kind of issue, actually. How do we make this transition to the right kind of AI?

Yves Saint James Aquino:  I agree. And just to echo on that, especially what we've learned, what we have experienced during the pandemic about a lot of parts of the Australian healthcare system. They're really interested in the advantages and potential benefits of artificial intelligence and how it can automate things as well as support workforce, because at the moment Australian healthcare workforce would really need a lot of help, especially when it comes to screening programs. But at the moment what is happening is that Australia tends to import a lot of these systems instead of developing our own. And there are benefits. There are trade offs when it comes to that.

But one of the key challenges when doing that is that these AI systems developed elsewhere are built on data based on the local population and people assume that it's like any other technology where you can copy/paste the technology from one area to the next and have no problems. But as we are finding out, we need to understand how AI systems work in local populations. So I think that's what we have to look out for in the next few years, not just the excitement about the advantages of AI, but how can it work best within the Australian context.

Lisa Smithers: Can I pick up potentially, Yves, on your some of the things you're saying there. AI is built on data most of my work has been on big data really more administrative sources of data. And those systems can't work unless we get data quality right in the very first place. So based on my experience, I think over the last 15 years of using administrative data, I would actually propose that the quality of that data has improved along the way. But I think that it still depends a lot on how data was set up, who set it up, for what purpose and how it's used by people entering that data. So that sort of fits a little bit with what you were saying Yves.

My area is perinatal health, and so with administrative data, that perinatal data is collected extremely well across the whole of Australia because we have standardised definitions and fields, we have really good reporting systems for feeding up the quality of that data. And yet, although administrative data is great for these purposes, it's collected with a health service in mind.

Stacy: So I think that's something we really need to think about. If we think about the potential of AI sitting on routinely collected data. And perhaps just one more thing I wanted to mention here is what I perceive as being a current and potentially a future problem is having data analysts, fully qualified people who can actually do the work of analysing the data.

So most organisations are collecting data of some nature. Every organisation needs people to analyse that data. So who's going to do this work? I think we still don't have enough well qualified data analysts to be able to do this kind of work. So I think there's a gap in the market here, and although UOW is trying to do it, it's really hard to find people who know and understand these systems to be able to just design them.

Alberto: And just very quickly add to that not only who's going to do it, but they have to be well rounded, right? Not only number crunchers, then that's something that we need people and everybody needs to understand. Because a number cruncher without a well-rounded idea of how it's going to impact is not going to be the kind of people we want creating the systems.

David:  Yeah, it's so true. And, you know, as we think about that, these are not biostatisticians. This is not what we've been training for the last century. This is a new workforce that can deal with very large numbers with new tools.

Stacy, I'm really pleased that that people are still training radiologists. I think there's a new axiom in the 21st century, which goes 'artificial intelligence will not replace doctors, but doctors that don't use artificial intelligence will be replaced'. And and so as we we think about the the challenges of the future, how do we prepare a workforce not only, as Lisa says, for the the analytic programs, but as you've pointed out, Yves, how do we prepare a workforce to actually understand and interpret the outputs of these programs? Are we changing curricula fast enough in order to do this?

Yves: Mm hmm. Well, this is a very complex question, David, but for me in an ideal  world, there shouldn't be hard walls or borders between disciplines. And they think there. I mean, there is still a value for general education in general subjects and more technical courses still having some element of social sciences, because as we know, and this is the case for courses like medicine as well, if you don't have any understanding of the social implications of medical or clinical practice, you might not have the tools for empathy to be a more empathetic practitioner.

And I think that's true for data science and more technical courses. We need to be able to explain to them, or at least teach them a lot of the social issues that they probably will not be exposed to from studying and then practicing. So at the moment, that's one of the struggles or challenges that we have discovered in our study, is that there is difficulty in communications between experts. So data scientists have different language versus social scientists versus regulators versus public health experts. And they think we need to empower students to be able to discuss things from experts from another discipline. But I understand that will take a lot of work, but that would be my ideal scenario.

Alberto: And, you know, the other part that we need to be doing and at least we're trying to do here in our Bachelor of Data Science is that it's a full data science, right? Not just data, but science needs to be applied. There needs to be context. There needs to be a yearning for understanding the context to then be able to apply any technique.

It's again, not just techniques for the sake of applying techniques, but what is the context? Do they make sense? We're just getting the data to to be within the context of the problem. And that's how you start realising, you know, that you can get people, you know, to really work in industry or in health. David touched on, you know, the biostatistician tells us of a rare species who kind of tries to straddle the worlds. Right. And I think that's the type of not fully curriculum per se, but formative education that we need to be giving the people that we are creating now so that they can straddle the worlds and be useful.

Stacy: And it really needs to be at all levels of responsibility, doesn't it? I mean, one of the things that we've talked about a lot in the empirical work that we've done with all kinds of stakeholders that I've mentioned before is who should ultimately have responsibility around these systems. And I think that the final answer usually is everyone's got some responsibility, that the right question is actually which responsibility does this person have? So clinicians need to have the skills to be able to evaluate should I be using this tool with my patients because they have a duty to their patient, know they actually have an ethical responsibility to their patient, to know that the tools that they're using are doing what they think they're doing and they're not going to cause harm.

Hospital administrators who procure systems, they need to actually understand what they're buying and not just be sucked in by the hype of the developer, if that is an issue in a particular case. Regulators often really struggling with these systems because they present challenges that weren't really a problem previously when regulators were trying to do with medical devices.

So we've got an artificial intelligence system that can adapt constantly, can change itself all of the time based on new data that's presented to it. That's a much more difficult problem for a regulator to know how to manage, then back in the day when it was really just a physical object that if something went in, then same thing would come out. You know, it was it was a much more predictable beast to try to regulate, whereas now regulators are having to deal with the complexity of potentially changing systems.

And then there's the community like we have all discovered ChatGPT in the last year has become part of the public imagination. And all of us, I think, need to become aware of how AI's working because it's not always obvious that AI's in play, right? AI can be making quiet decisions in the background, so it's really important that everyone is aware of the, the fact that AI is everywhere. And in fact healthcare has been pretty good at being really careful about allowing AI in because healthcare has certain standards. It's helped to hold AI back and to ask, 'Is this good enough yet?' AI is much more prevalent in a lot of other areas of everyday life.

David: So, Stacy, both you and Yves touched on firstly the the inherent biases that can be in artificial intelligence if we don't build it properly and if we don't use the right populations to teach it as as Yves has pointed out. I think that leads very logically to a question around the ethical implications of collecting and using data, because if the data aren't being applied to the population where artificial intelligence is itself being applied, then you know, how do we move forward? So is is there a social license in Australia today for the use of of health data to improve health services and to teach and refine artificial intelligence?

Stacy: It's such a great question, David. So at the Australian Center for Health Engagement, evidence of values, we kind of specialise in a in a process that takes information to the community and asks them to work together to make recommendations about what should happen. And these are called community juries. So we we ran a series of community juries that were led by Annette Braunack-Mayer, who's a Professor in our center.

A year or so ago about sharing data from the health system with private companies for research and development. So it's not always the case that these AI systems are going to be developed by private companies. Sometimes they might be developed inside of health services, and there's often very entrepreneurial and innovative clinicians who notice a problem in their health system that they think that AI could help with. And they have the skills and they start to develop an application or there can be small spin offs inside universities. So things are things aren't necessarily purely kind of big tech or private, but we talk to people about sharing health data for R&D and private companies.

And interestingly, part of this process is people learning. And the more people learn about sharing data and what good can come of sharing data, the more willing people are to support data sharing. So that's a general kind of pattern that has been seen in a number of these similar processes around the world. So when people understand the benefits, they are supportive, but always with caveats. There's always quite strong conditions around that sharing. It's not just, I'm sure, go for it, share my data.

So generally the Australian process people said it has to be for public benefit. You have to be able to show me that this will actually do good in the community. It has to be done responsibly. There has to be a clear accountability framework. The data have to be secure that would really matter to people. We have to manage these data responsibly. There has to be proper penalties for misuse. You really have to make it hurt if people use these data in a way that they shouldn't so that there's a real reason to prompt them to be careful with these data. So there's a clear recognition of the value of the public benefit that can come from this use, but also a real knowingness about the value and the importance and the significance of these data for us and the need to be really careful about who uses them.

Alberto: Yeah. I mean, just a very quickly on data and you did touch on it, but is that need for people to feel comfortable about it, right? What are the processes in place for that data not being hacked, the data not getting access from other places, not being used for things that, you know, I may not really be happy. And we're again, with an ad, we're doing some other project. We're still on the analysis session part of it, but that's one of the things about, okay, what do you believe it should be used for? What do you already think it's being used for? Right. That's the other part.

A lot of of people give license when they think, oh, it's already being done, so what am I going to do? And a lot of people, you know, at least in some of the focus groups, apart from the surveys, you could see that tension about it's not necessarily consent per say, but what is the safety? Why do you do security? What is the confidentiality? What is the privacy? And those issues have to go hand-in-hand, I would say, with the benefit. Right? Because some people are like unless you guarantee the safety of it and security and the privacy, I don't know if I really care so much about the benefit. 

David: Yves, your thoughts? Because this is an area in which you're you're working all of the time.

Yves: Yeah, thank you so much for that. And in support of what Stacy mentioned as well, based on my conversations with different experts, I think they are aware that a lot of members of the society tend to mistrust the government and some private companies because of the recent examples of data breaches which are quite high profile. And if they don't understand the mechanisms that protect their data and the benefits on sharing their health data, they might not support it. But I think at the moment it's still unclear who really owns what anyway.

And I think for some experts, they believe that patients don't care. They always share very private information on social media anyway. But that's a view that we need to challenge as well, because some comments like some thoughts are not equivalent to health data, right? So some people might share what they eat for lunch, but they're not going to share their, you know, medical conditions or their age. So I think there is that misconception that just because people are freely discussing stuff online on social media, that they're just going to share whatever is in their personal health records.

David: And Lisa, I want to come to you for a moment because you deal with pediatrics, with neonates, newly born bubs right through. And they don't have a lot of say in how their data are used as far as I can tell. How do we as a community seek a social license in that space to ensure that we're actually using data as as people would want?

Lisa: Wow. That's a very tricky for me to address. But I do agree. Part of the the baby's data comes from the mother. Right. So in some way, the baby must have some right to the data from the mother as well. Which is it? Which is an interesting thing that's come up with an ethics committee that I've dealt with in the past, that if we're dealing with pediatric outcomes, we do need to know something about where the baby has come from in the circumstances in which they were delivered. But I think this is more a question for the Ethicist!

David: Well done. Great. So who wants to take that? Because it really is incredibly important as we think about social license, we can talk about people who can gift their data to the greater good. But what about those who don't have a voice?

Stacy: I'll give Yves a chance as well. So generally for people younger than a certain point in adolescence and depending on what kind of decision you're talking about, that point in adolescence can shift choices about all kinds of things, including what happens to your day to rest with the Guardian, who is usually the parent. So generally it's left to the adult to make the decision about what happens with data.

Then at a point in adolescence, depending on what decisions are being made, at least part of the control begins to go to the person themselves. So and it really depends on the the kind of data that are being shared and the kind of situation that you're in. So, for example, if the purpose is clinical care, then the young person might have control of their information a little earlier than if, for example, the purpose was for research.

So things can be different depending on the situation. But often I think this is partly about individuals and it's really important that individuals have control over their data and have an ability to have a say about how the data are used. It's also about the community. You know, all all of this really, we can call on big ethical concepts like the importance of confidentiality, the importance of respect for autonomy, so that people have the ability to make things go the way they want them to go in their life. And that and they're very important concepts and very widely shared. But really in terms of the way that we practice, a lot of it comes down also to a public conversation and what people are willing to sign up to as the social norms and they don't drop out of nowhere.

You know, they're actually part of a form of engagement really with the community. And as we saw in the community juries, you know, when people understand what's going on, their position will shift. You know, they'll make a different kind of judgment about what's the reasonable thing to do. So I think it's helpful to think of all of these things as a conversation, as needing a conversation, and us needing to engage communities and bring them into these considerations. But Yves, what about you? You've you've done a lot of medical ethics training over the years, what do you think about young people and their data?

Yves: I totally agree it does depend on the age. So the younger the patient or the health consumer is usually it is the guardian who has the control over what to do with the data. But at the moment there are also conceptual and philosophical conversations about what data are we talking about? Because there is a difference between personal data and sensitive data. I won't get into the definition, but so those kinds of classification of sensitivity, that will also impact on whether the responsibility is on the patient or the guardian. But just letting you know that this is an ongoing conversation.

It's not just about social license and people agreeing about sharing their data, but what happens once they share that data? Where does it go to this? It go to a private company? Does it go to the government? Will it be commercialised or monetised, or will it just be used for research? So I think these are massive conversations that you can't really explain quickly.

In an ideal scenario, if you're encountering a patient for the first time and you're collecting information, that's usually at least in the clinical context, that's where you explain where the data might go. But not everyone has the, you know, luxury of time to explain. Here I am collecting raw data now and this is where it might go and this might be the secondary use. It's not just for your clinician, but eventually your data might be used for other types of research and then expanding the benefits. So these are really giant conversations that can't be encapsulated in a very short clinical encounter, unfortunately.

David: So we've got a couple of questions from from people who are watching today. And I really do like the first of these, 'How do we stop artificial intelligence, exaggerating pre-existing biases in data collection?' There's a good, solid ethical question for you.

Alberto: Well before the ethicist says something. Well, it impacts a lot and Yves and I are working on how do we actually try to get the word algorithmic bias to be thrown out of the vocabulary. Right. Because, A, the algorithm itself is not biased. B, it is the generative process of the data that could have the social or racial or whatever bias in it, right? So one thing is how do we create collection methods that can do away with what we know are usually biased variables, variable settings.

Second is how do we train our data science tools in a way that we could again do away with some of these and still get the correct signal? Right? Because so far and that's the part where, as I said in the beginning, I don't really think we're at the point of intelligence. We are at the point of pattern recognition, so all the tools we have right now, the faster pattern recognition, and if the data is loaded with a signal that it has a social bias. The pattern is going to be recognised. So that's about all we need to work out. The generation of data, the process that generates the data, the process that collects it, and then the process that looks at the patterns to see can we do away with some of these things that are way to be seen telling us something that's wrong?

Stacy: I'm so glad, Alberto, that we need to stop calling it artificial intelligence. It's such a shame that that name really caught on, isn't it? Yeah, and it is actually very misleading. But I'm going to throw straight to Yves because here's a lot of work on both socio legal and data science approaches that mitigate bias, so over to you Yves.

Yves: So thank you so much, Stacy and Alberto. And one of the issues that I've discussed with the experts say I've spoken to was the problem of algorithmic bias. They mentioned data science mechanisms, so the things or approaches that you can do to de-bias, for example, an existing model or a model that is under development that I think is more of Alberto's expertise. But when people talk about social legal approaches, these are approaches that you can do outside data science, because as we know, when you talk about bias, biases in outputs of models, it's really based on the data that is already biased. And the bias data is really based on the healthcare system. So whether it's Australia, United States or United Kingdom, we know that the healthcare system has a lot of inequities, whether it's under servicing already marginalised groups or over servicing some marginalised groups.

So there is already data asymmetry that exist in the healthcare system. The other issue is in terms of what consists of experts that exist in data science community, but also in areas of decision making, whether it's in policy making or regulation. A lot of efforts coming from, for example, black in AI or women in AI have criticized these bodies as being exclusively a certain type of person and often the certain type of person are not aware of the impact of technologies on marginalised groups or are not aware of the existing injustices that contribute to the biases. And they are calling for more diversity in the workplace across the board, in any kind of workplace that is involved in the development, research, deployment or regulation of artificial intelligence in healthcare.

David: The other question we have here, and I'm going to paraphrase a little, but at the moment a clinical diagnosis is almost a black box from where the patient sits. You know, how do people arrive at that diagnosis? Is there an opportunity and indeed a right for patients through AI, artificial intelligence assisted diagnosis, to look into the black box, to actually see some of the workings that are helping clinicians to to make those diagnoses?

Alberto: You you know, this happens if no one goes for it, I just open my mouth. I may be a little bit devil's advocate here, the black box has existed before AI, but most of the time on a 5 to 10 minute meeting with your GP, there's so much and I think you kind of alluded a little bit to this in another sense Yves, you don't have enough time to go through the full discussion of, well, basically all of this is that I can put your diagnosis and I can tell you it's definitely not this because of that. I mean there would have to be a half hour appointment, right? So in that sense, it still kind of exists.

Now, I'm absolutely saying it ought to be that everybody has the right to know what's going in, even if it's, again, just with your GP, whether AI-aided or not, I the potential problem we may encounter is different AI or machine learning tools have different levels of explainability of interpretability, so even if there's a desire to, it might be really hard, just as it may be really hard for a GP to actually explain the overall interpretation when you have a pleural effusion or something like that.

David: Great. I think that's a wonderfully fulsome answer. We've touched a couple of times in the conversation so far on the quality of the data. What goes in dictates in many ways what comes out at the other end. Are they gaps in the way that health data are collected? And if so, how should we address these as we rely more and more heavily on artificial intelligence moving forward in health?

Lisa: Maybe I'll tackle this one first. I guess in terms of gaps in data,  I've got a couple of things to mention about that. We've seen a massive move in health services towards electronic management, electronic medical records, so the collection of data electronically. If health services aren't already doing that, they're certainly aiming towards that. And I think one of the difficulties as a researcher who sits outside the health system isn't knowing what data is being collected. And I sort of alluded to this in the beginning as well when I mentioned that the collection systems that we have are based on what the health service needs, not necessarily what we might want as researchers or even what the patient might want. So getting a seat at that table to decide what data is going to be collected I found, is extremely difficult. So if there's a solution to this, I'd like someone to tell me. I haven't figured out how to do it yet.

And the other thing that I wanted to touch on in terms of gaps in data collection is that I don't think, at least in my view so far we've done very well at all or got very far in collecting patient reported outcomes. I think if we are intending to have patient centered care, then we need to know and have patient reported outcomes. And if they were part of the system like the the electronic medical record, that kind of information might be collected more frequently, more systematically using some of the systematic tools that we have for patient reported outcomes that would benefit patients because the health services could then potentially use that to improve their care in areas where it's potentially not as good and they can do it evaluation so that just two little snippets of my opinion on where this could go.

David: Fantastic. Lisa. I mean, patient reported measures, including outcomes and experience, are critical and health systems around the world are starting at last to invest in that space and to respond to the feedback that people are providing. And I think it's that latter bit that will not only improve the quality of those data, but also encourage people to engage in that process.

Lisa: And I couldn't agree more, David, because I think it is about you don't just collect data for the just collection purpose itself. You have to want to do something with it. You have to be able to do something with it. And that really, I think is the most important part.

David: Categorically, yes. Stacy, thoughts on this?

Stacy: So I just wanted to build on what Lisa said about data and collecting data for a purpose. So I think that needs to pull through to artificial intelligence as well, right? Because it's really easy for artificial intelligence to be built because there are data that are easy to build it on. And because it's an easy application to build with data and we've seen quite a lot of AI developed for that reason I think because data are readily available in that space and developers want to develop AI, that's their job.

You know, it's exciting to develop a new app. It's exciting to think that you might be doing some good by focusing in the health space if you've been working in other spaces before, you know, so it actually often is very altruistically motivated, I think. But just like Lisa said, the data have to be collected for a purpose. I think that AI has to be developed for a purpose, and that purpose needs to be driven by clinicians noticing gaps in health systems, patients saying this isn't working for us, communities saying this is a really important goal for our community. So it needs to serve that purpose needs to be pulled all the way through I think.

Yves: And they think some of the frustrations of overseas developers trying to get into Australia. They mentioned that there is lack of integration of data amongst states, not even within the same state, but different in a hospital or health service institution. There is lack of integration and it's sort of it is a roadblock. It is an obstacle to really take advantage of the potential of health data if every institution has a different form or is not connected.

It's a frustration for researchers, but it's also frustration for patients because they feel that if they move to another institution or to another state, they have to say the same thing, when they were promised that once we have digital copies or electronic medical records, that will lessen this burden. But that hasn't really happened yet. So there is frustration for different stakeholders.

The other issue that we are trying to look into, and this is something that Alberto mentioned because a lot of the data sets are collected for purposes of clinical service, there might be some missing information. So we mentioned about bias and one way that people have suggested to combat bias is that we need to increase diversity of datasets, right? We make sure that marginalised groups are represented in the datasets. But the question remains what do we mean by diversity? How do we represent social groups or marginalised groups when that information is not yet collected? So think about the information about race, these are sensitive information, and at the moment, even about gender and sexual identity, these are not collected. So we are trying to develop a project where we examine should we or should we not collect sensitive information to improve the diversity of datasets, hoping that that response can also minimise bias. So there is that ongoing conversation, not only what we're collecting, but what we are not collecting from our citizens, from our from members of the community.

Alberto: I think it lands back to what Lisa and Stacy were saying, the purpose. So just as we need to get purpose for the data we're getting, we should have a reason for not getting certain data rather than then just blindly ignoring it because people are going 'Oh, we can always link, right? But linkages have already, there's a huge area and linkage error and not, as you were mentioning, Yves, within the state you may not be able to link within different health places. Think about judiciary, education, right? If you really want to be thinking of holistic help on on what you're going to do for your healthcare, that's the other part where we're falling apart.

David: And as we think about that, you know, I'm reminded that there are some European countries where it is illegal to collect race.

Yves: That's right.

David: At one level, you say fantastic. At another level you say, how do you build artificial intelligence where you can guarantee that that algorithm is going to meet the needs of the entire community and know with it leads to some interesting challenges in areas with which I've been associated in cancer surveillance, in screening, participation and outcomes. You know, in Australia we do not collect any data on someone's cultural or linguistic background with the cervical screening program. And as you've pointed out, Alberto, linkages is not going to to fill that gap perfectly. So it has some very big implications for people.

Another question from one of the people online, and again, to paraphrase, we've talked about artificial intelligence, the need for good data. This question relates even further upstream. 'What about the the investment in the hardware and the actual process of collection? How do we get health systems and indeed other systems, as you've just alluded to, justice, education, community services to invest in in sufficiently robust systems for collecting it in the first place?'

Alberto: That question in itself had a lot of pieces, right? And so I'm really right now thinking about. I know where to start. Any help is welcome because...I'm a little blacked out right now. Could you just repeat that?

David: How do we get the the investment in the hardware, the processes, all of those things. I'll start off if you like...I think there needs to be a value proposition again, that that the end product is so valuable to to health, to patients, the community and to health systems that it becomes a no brainer almost.

Alberto: But the part where I think there's a lot more public than what the wording of the question says is that it's not just an investment on making the tool easier to implement, you know, getting a better stethoscope or better imaging. It is we are in an economy where you need to take away from one source to put in the other source guide, which then it's thinking what is the value that it's really going to bring? Because maybe we go back to the hubris of five years ago where, okay, it's going to give me no error and it's going to give me the perfect diagnosis and the perfect treatment. Okay. If you're going there, sure. Mobile where you're funding in together, getting better hardware. Just just making a farm for your predictions and for your treatment ideas. Right. But that's the problem, right? At which point are we going to saturate? And again, if we're still depending on that data. And so I guess I'd rather than hardware per say, we need to invest in intelligent data collection, quality, safety and transmission processes.

Stacy: And kind of integrated and organized systems that that don't overlap, that don't conflict with one another. There was some great work done in the U.S. about ten years ago by Wachter on the effect of digitization on doctors and the way that digitization actually came between doctors and their patients, because it creates what we always talk about autonomous systems.

We talk about AI is making our lives easier, you know, it's kind of like The Jetsons. We're going to be able to delegate all the bits we don't like to the AI, and then we'll just get to kick back and do the fun stuff, whether it's in a professional context or in our personal lives. But actually, the research shows, the socio technical research shows that that really what it tends to do is just delegate different kinds of work to the humans. And that's the work that it takes for the humans to create the inputs that the AI system needs to do what it does.

So there's a tendency actually just to move the work around or create different kinds of work. So I think in thinking about investment, I I don't know, I think you're right, David. It just has to be a really good business proposition to get the investment. But in in strategising that investment there also really has to be an eye to that kind of streamlining that can make it so that the humans aren't just there to serve the system, but the system is actually serving the humans. The kind of system is really important.

David: I love that phrase that the system is there to serve the humans and we mustn't lose sight of that as we struggle with a world that is going to evolve very quickly, not as quickly as we perhaps thought five years ago, but it will still evolve quickly.

Which really leads us to the the ultimate question for the afternoon, which is how can we work with the community, with policymakers, professionals, healthcare workers, researchers to actually realise the potential of big data turned into artificial intelligence? How are we going to, as a community, take those important steps forward if we're going to, to really see the benefits that we hope for?

Stacy: I can start if you like, and then I'll pass to the others because I've done a lot of talking. So we're running a community jury really soon. This is in the AI domain. We're asking a randomly selected group of Australians. We're going to engage with them all over the country. We're going to give them information about artificial intelligence and how it can be used to detect or diagnose diseases. And we're going to ask them, under what conditions should we use AI for disease detection and diagnosis in Australia? After they've learned they're going to come together in Sydney, they're all going to fly from all over the country and they're going to spend a long weekend together deliberating on what should happen. And to my mind, that's the kind of engagement that we need, that we really actually need to bring the community into this conversation to help to make recommendations to guide policy making. And in fact, we have very generously we have support from the Royal Australian College of Radiologists, the Royal Australian New Zealand College of Radiologists .

David: Because we're still training them.

Stacy: That's right. And as we are, it turns out there are still radiologists and they probably always will be and they're really keen to support and they want to hear what Australians have to say. We've got a number of R-Techs which are big groups that connect the health system to the research system in Australia, funded by the National Health and Medical Research Council. We have three of those organisations from all over the country coming and those policymaking bodies. They want to know what Australians have to say about these questions. So for me that's the way forward, that kind of partnership.

Alberto: So just building on that because obviously, you know, the real patient point of view on integration is crucial. But the other thing that I think we still live in a society where there's providers and customers in a way, and we need to move away from that. You know, we don't need to think that policymakers are going to be the customers of the product that researchers and data scientists have to produce to give to them.

We need to be thinking of just as we integrate patients to get their ideas and the population. We need to be working really, really together from the get go off is this research that's also going to have already a vision of impact on policy and then have policymakers in the group right, rather than saying, okay, well now we created this has know suppliers, we created the data, we created the output, we're going to the policymakers. Here you go, it's in your court to play with it and see what we can do. Right. And that is one of those things that we'll start getting the circle to actually feedback onto itself and I think make a better a better sense of developing the AI with a purpose and with potential policy implications going forward.

Lisa: Yeah, I guess my my favorite way of working is to work with clinicians or practitioners, health practitioners. And so I really enjoy that because that brings questions to me that are definitely relevant to their situations in their day to day practice and where I feel like the translational impact is most powerful because they have the potential to change those systems from the inside. So that sort of flows along the way with what we're talking about here that is just for me is the most rewarding as a researcher, and I just thoroughly enjoy the challenge of getting to know their fields and how they operate and what the issues are so that I can do my little piece towards making that bigger impact.

David: Yves?

Yves: Thank you so much. I think Stacy, Lisa and Alberto have said a lot on strategies and I think co-design is very important, but also just making sure that our research doesn't remain just within the university. I think University of Wollongong is good at really sharing what we are finding out into the world and I think the public, we should empower the public to understand the issues and not just as part of our projects but just the public in general. Share your research. What are your findings? How is it impacting or how would it potentially impact the lives of Australians?

I think we have to be more active in sharing our research and not just being siloed in our office. And I think that that's what really inspires me as well, is if there's something that we find in our studies that we can share that with the public. We're not just working with the public, but we're also making sure that they have the information. They can also access the information that we gather through our empirical studies.

David: It's imperative that this is a whole of community conversation and that we're sharing openly and fully what we find and and how we have found it. It's a bit like, you know, Year 8 maths.  You might get the right answer, but you've got to show the working as well. And I think that's where we have not done well as as researchers in communicating and and working alongside the community. We've only got a couple of minutes left, so it's up to me to ask the fun and very obvious question and to come full circle. Will GPT have any impact on health in Australia? 

Lisa: I'm enjoying it so far. A little anecdote, as many of you here on the panel know, maybe the audience don't we have a new MPH that we're currently starting now and we have a big data specialisation within the MPH, so check it out. I'm just doing a quiet plug there. But with the new MPH, I'm developing a new subject and so there's all of this ChatGPT. So I'm thinking, all right, what is this thing? So I signed up and I thought, I know I have to create a tutorial, so I'm going to ask ChatGPT what is selection bias? And ChatGPT comes back with this nice stream on selection bias, which is exactly what some of the panelists were saying before. It repeats essentially regurgitates what's out there on the internet. But some of it was actually wrong and I thought, admittedly my students are doing this, so don't listen to ChatGPT, "you're wrong. This is incorrect". And so it comes back to me in apologise. Yes, I was wrong. This is the correct answer. So here is going to be a lesson for the students in my class. I hope there's none in the audience about the use of ChatGPT. And so I'm trying to get wiser in what it does, how it works, and how I can use it and teach people how to use it. So that's one little anecdote.

David: That's beautiful. I'm totally with you. If we think about the first time any search engine came out or even nowadays. Three, five different people are looking for the same thing. Three of them get to it first, Right? So knowing what to ask, whether you have a faster because that's really what ChatGPT is, it's a way, way, way, way faster collation. Right? It's not intelligent yet because the semantics are wrong. Then our exercise is going to be on being intelligent when we ask people to be intelligent, about to ask GPT to produce. 

Lisa: Yeah, I think maybe this will improve over time. I'm hoping it does, because I know that my use of it will drop away if I don't see it doing things that are correct. Yep. So that's just my personal view. And I've had a couple of a look at a couple of others as well. Some of them I haven't been particularly impressed by, but yeah, let's see how.

Yves:  And I think there is an ongoing conversation how different it is from, say, Google search. So we'll find out their ongoing research about how a patient can use it or how a clinician or a public health expert can use it. And there is ongoing research on that.

David: I look forward to to seeing that. Please join me in thanking Lisa, Alberto, Stacy and Yves for joining us today and giving us a great insight into the brilliant research from across the University of Wollongong.

Thank you also to you, our audience, we hope you enjoyed the discussion. The event was recorded so everyone who registered will receive a link to the recording through email. I'd finally like to thank Jill McGarn and her team for bringing this together and the excellent work they're doing behind the scenes to bring the Luminaries program together. Look forward to seeing you in two weeks time. Have a great evening. Thank you so much.