Optimising Care or Automating Inequity? AI in Australian Public Healthcare.

Author : Dr Arosha Weerakoon

Abstract : Artificial intelligence and machine learning are increasingly positioned as low-cost, efficient solutions to overburdened and underfunded healthcare systems. In Australia, AI-enabled tools are beginning to shape oral health surveillance, risk stratification, triage and decision-support, with the promise of reducing workforce constraints, enabling targeted service distribution and mitigating unmet need. Yet these efficiency gains may come at a cost to equity, with ethical implications for both those who receive care and the workforce that delivers it. This presentation examines an Australian perspective on the use of AI in health settings to explore the tensions between deploying technology to ostensibly optimise systems, while simultaneously amplifying and perpetuating inequity. Using Australian-focused healthcare and public health perspectives, it explores how data quality, representativeness, algorithmic design and implementation environments may differentially affect priority populations who already experience disproportionate oral and general health burden. The presentation is offered as both a provocation and a primer for discussion, inviting critical reflection and the sharing of knowledge and perspectives from an international audience.

Keywords : AI in Healthcare: Balancing Efficiency, Ethics, and Equity in Australia

Conference Name : International Conference on Community Health and Epidemiological Research (ICCHER-26)

Conference Place : Colombo, Sri Lanka

Conference Date : 10th Mar 2026