Data, artificial intelligence, and other health technologies

Our research into health and big data

The ACHEEV Team talks about the relationship between health and Big Data

Annette Braunack-Mayer [00:00:03] Every day we produce large amounts of information about ourselves through our interactions with government agencies in ACHEEV we're exploring what governments should be allowed to do with our data, who they can share it with 

Belinda Fabrianesi [00:00:16] and what ordinary people in our community think about these questions. 

Jackie Street [00:00:20] To take one example, health departments should be able to use our own information to provide appropriate treatment for all of us. But at the same time, I think most people believe that health departments should be able to combine everyone's information to improve services and the health system as a whole. 

Rebecca Bosward [00:00:37] But what about combining everyone's hospital records with their education records or housing information 

Belinda Fabrianesi [00:00:43] or giving our data to a pharmaceutical company to develop new drugs or to monitor the safety of drugs that are already available? 

Annette Braunack-Mayer [00:00:50] And the whole field of big data is changing so rapidly that there will be new uses for our data, new organisations and people to share it with and even new data sets we hadn't thought of using. 

Rebecca Bosward [00:01:01] It's not surprising that some people are concerned about using government data in this way. We could lose control over where or how our personal information is stored, and this could lead to a potential violation of our privacy.

Jackie Street [00:01:13] Our research suggests that people mostly worry about discrimination and embarrassment if their personal details were revealed. And this has the potential to undermine the public trust in the service providers and the system as a whole. 

Annette Braunack-Mayer [00:01:27] So we're asking community members what they think about these issues, and we're feeding the information back to the agencies who make decisions about data sharing.

This theme focuses on how data, and technologies like artificial intelligence, will change our health futures.

Data is now at the centre of human lives. Data allow humans to visualise, measure, monitor, intervene, predict, plan, communicate and much more. We all generate masses of data every day—whether we know it or not—and these data are valuable to many different interests. From data, developers are building artificial intelligence-powered technologies designed to support or replace human workers in healthcare systems. Health services have always involved technologies of some kind—ranging from ancient tools to modern imaging machines—but healthcare artificial intelligence, built on healthcare data, promises a new and transformative kind of health technology.

This raises big questions: not least, can the promised benefits of data use and new technologies ever be delivered? And if they are, what harms might they also cause, and who will be harmed? Using innovative social and deliberative research methods, and ethics and social science analysis, we generate new frameworks and recommendations that reflect what matters to patients and communities, to make health data use and health technology better.

Our goal is to produce new ways of thinking that will reduce harm, increase benefit and promote justice in health data use and health technology.



Project Details

Machine learning systems—algorithms or forms of artificial intelligence (AI)—are increasingly able to contribute to, or even take over, diagnostic and screening tasks.

This project responds to the need to prepare for the ethical, legal and social implications of diagnostic and screening AI.

Our team includes ethicists, social scientists, lawyers, clinicians, public health academics, health economists and data scientists.

We will focus on two cases where machine learning is well-developed: breast cancer and cardiovascular disease. This multi-method project engages with diverse stakeholders to understand, from their perspectives, what is happening and what should happen in diagnostic and screening machine learning technology.

We are interviewing a wide range of stakeholders, holding dialogue groups with service users, conducting discrete choice experiments, running community juries with members of the public, and undertaking fundamental ethical and legal research.

Based on this we will develop strategies to address the ethical, legal and social implications of diagnostic and screening AI.


NHMRC Ideas Grant 1181960, 2020-2023, $823,476.40



Project Description

This multi-phase project applies, for the first time worldwide, cutting-edge AI technology to ‘real world’ breast cancer screening practice. Colleagues at Curtin and the University of Sydney will conduct a novel comparison of AI and human readers using datasets that are representative of screening populations, and will conduct a cost-effectiveness analysis of using AI in breast cancer screening. At ACHEEV, we will run dialogue groups with women about how AI should be incorporated into breast screening program design, and what factors make the use of AI more or less acceptable to women

Project partners

Dr Luke Marinovich (Curtin University), Professor Nehmat Houssami (University of Sydney)


National Breast Cancer Foundation Investigator-Initiated Research Scheme. 2020-2022, $822,561.28


Project Details

AI has been widely used in industries including finance, marketing, communications, human resources and policing. It is now making its way into other sectors including health care and social services. Few researchers have investigated what people think about the adoption of AI. This project employs a novel survey methodology to examine whether Australians support or oppose the adoption of AI in health and social services, and what aspects of AI implementation they think are most important.


2019-2020 ($49,239), University of Wollongong Global Challenges Project Grant


Project details

Our aim in this project is to increase knowledge about the experiences of users or motorised mobility devices (MMDs), and the everyday meanings of MMDs for users. The project is designed to provide empirical evidence that will be useful in informing planning and policy agendas in transport, disability, health, infrastructure planning, and the types of MMDs designed and sold in the future. This is a multi-stage project: ACHEEV researchers will lead a deliberative engagement with MMD users in relation to a future urban planning project, as a practical experiment in inclusive participatory planning.

Project partners


Project website

Let's all move together


ARC Linkage LP180100913. 2019-2022. $356,000