Indigenous-Led AI for Stronger Aboriginal and Torres Strait Islander Healthcare

AI in Aboriginal and Torres Strait Islander Healthcare: Early Findings Call for Indigenous-Led Design and Governance

7 October 2025

AI can support better care in Aboriginal and Torres Strait Islander communities, but only if it is guided by Indigenous voices, data, and decision-making. A scoping project led by CSIRO with Indigenous partner organisations engaged 53 leaders, clinicians, researchers, and health service providers across four workshops (2023-2025) to define what safe, useful AI looks like on Country and in community-controlled services.

Current AI frameworks are often too general and miss critical cultural context. As one project lead put it, "If AI is to benefit our mob, it must reflect our voices, our data and our ways of knowing. Without Indigenous-led governance, there's a real risk that AI will perpetuate bias and repeat the mistakes of the past."

Three priorities for responsible AI in Indigenous health

• AI health literacy and cultural appropriateness: Ensure communities understand how AI works, what data it uses, and how it supports day-to-day care. Build plain-language education and culturally safe explanations into tools, consent, and clinical workflows.
• Indigenous data sovereignty: Health data must be held, governed, and used under the custodianship of Aboriginal and Torres Strait Islander organisations, with clear data access, storage, and benefit-sharing agreements.
• Self-determination in design and oversight: Place Indigenous organisations at the centre of AI design, implementation, evaluation, and governance from day one-not as stakeholders, but as decision-makers.

These priorities point to a simple truth: effective AI is cultural as much as it is technical. "We know that Aboriginal Community Controlled Organisations can use AI as a powerful tool to support and strengthen their work, but it's imperative that our Mob are in the driver's seat to ensure true self-determination," said Dr Jill Gallagher, CEO of the Victorian Aboriginal Community Controlled Organisations.

What this means for healthcare leaders and clinicians

• Co-design with Aboriginal Community Controlled Health Organisations (ACCHOs) before selecting or building any AI tool. Budget and schedule for iterative community review.
• Establish formal data sovereignty agreements that specify custodianship, storage location, access controls, secondary use, and community benefit.
• Set up Indigenous-led governance for AI use (e.g., an ACCHO-chaired board) with authority over procurement, validation, audit, and decommissioning.
• Require cultural safety criteria and bias testing in procurement. No pilots without evidence of performance across relevant subpopulations.
• Integrate informed consent that explains model purpose, limits, data inputs, and alternatives in clear, culturally appropriate language.
• Fund workforce capability: frontline AI literacy, clinician education, and roles for Indigenous data stewards and clinical informaticians.
• Plan evaluation beyond accuracy: measure care access, patient trust, cultural safety, and community-defined outcomes.
• Prioritise interoperability with ACCHO systems and processes so AI augments, not disrupts, continuity of care.

Project partners and next steps

The project was co-led by CSIRO's Australian e-Health Research Centre (AEHRC) in partnership with the Victorian Aboriginal Community Controlled Health Organisation (VACCHO), the Aboriginal and Torres Strait Islander Community Health Service (ATSICHS Brisbane), the Centre of Excellence for Aboriginal Digital in Health (CEADH), and the Australian Indigenous HealthInfoNet.

The team is now applying the findings to co-design self-determined AI tools in Aboriginal and Torres Strait Islander health. Early work focuses on community governance, culturally safe data practices, and practical use cases in primary care.

Helpful resources

• WHO: Ethics and Governance of AI for Health
• AIATSIS Code of Ethics for Aboriginal and Torres Strait Islander Research
• Build AI literacy for healthcare teams (courses by job)