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Presentation 1: “Why I’m tired of co-design, ‘engagement’ and ‘involvement’: Are we really moving into a participatory era, or just polishing the glass ceiling?”

Presenter: Dr Brett Scholz is a critical health psychologist whose work focuses on lived experience leadership in health policy, services, research and education. The majority of his publications are co-produced with and co-authored by lived experience researchers. Recently, his research program has been adopted by Canberra Health Services with their current research strategy which commits to going beyond ‘engagement’ and ‘involvement’ of consumers to a model partnership in which power imbalances are critiqued and redressed to ensure people with lived experience have decision-making and agenda-setting power.

Abstract: Understanding of the benefits of lived experience-led health policy, practice, research and education has been developing for decades. However, barriers to genuine, non-tokenistic lived experience leadership remain across the health sector. Research claiming to be using participatory approaches such as co-design and co-production have increased exponentially in recent years, but the extent to which these have been examples of true shifts in power dynamics is unclear. Models of engagement that do not redress power imbalances between people working from a lived experience perspective and other health professionals (such as advisory groups without decision making power) are relatively low bars. If we settle for mere ‘engagement’ or inclusion in cases where lived experience leadership in policy, services, research or education would have been possible, then we lose out on the potential benefits from the expertise of people with lived experience. In this presentation, I will discuss how we can all contribute to breaking down these power imbalances and move towards a more truly participatory era in health.

Presentation 2: “Powering Efficiency and Effectiveness in Personalised Precision Health with AI”

Presenter: Dr Hanna Suominen, MSc, PhD, Docent, MEdL, SFHEA is at the forefront of accelerating health impact from personalised precision medicine technology through the application of advanced Data Analytics and Machine Learning. She is a Professor of Computer Science at the Australian National University, (ANU), the Associate Director (Neuroinformatics) of the ANU John Eccles Institute of Neuroscience, and the Executive Leader (Computing and Engineering) of the ANU Our Health in Our Hands (OHIOH) strategic initiative. She previously worked for the ANU School of Computing as its first Associate Director (Engagement & Impact), establishing the portfolio. Before this, she was the Leader of the Theory and Applications in Multimodal Pattern Analysis (TAMPA) and Natural Language Processing (NLP) teams at Data61 of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the National Information and Communications Technology Australia (NICTA), respectively. Hanna has almost 20 years’ experience of working at the interface between technology, education, and health sciences, and is passionate about co-producing research and education with Lightcast and Konan Medical, among others. By bridging disciplines, professions, and areas of expertise, Prof Suominen is co-creating tools that will transform tedious tasks into AI-assisted workflows, thus releasing human labour for more meaningful duties and enhancing Australia’s prosperity.

Abstract: Powering early detection, marker monitoring, and disease management with Artificial Intelligence (AI) is providing substantial effectiveness and efficiency dividends in personalised precision health (PPH) by decreasing time demands and increasing the flow of diagnostics. During this talk, Professor Hanna Suominen — the inaugural Associate Director (Neuroinformatics) of the ANU John Eccles Institute of Neuroscience and the Executive Leader (Computing and Engineering) of the ANU Our Health in Our Hands (OHIOH) strategic initiative — will share experiences of her research program in bringing the next generation of AI-empowered PPH technologies to bear. For example, our excellence in co-creation and efficient evaluation of Machine Learning (ML) and Deep Learning (DL) algorithms allowed us to expedite visual field testing for checking brain health or vision loss over time; now we need to ask for just 82 seconds of the tested person and their clinician’s time to test 40 parts of the two eyes in a non-contact way. Furthermore, by transdisciplinary theorising and tooling of explainability and efficacy evaluations in ML and DL through Shapley value analysis, we have guided the identification, validation, understanding, and screening of cancer markers. These resourceful and responsible AI strategies and solutions for sensing and making sense of markers make PPH more sustainable and equitable. Moreover, their implementation as a deep analytical data science platform can accelerate discoveries in PPH while increasing the return-on-investment for related data and software resources. These contributions will drive systemic changes towards a healthier nation and societal prosperity.