Ethical AI in Public Health: A Governance and Implementation Framework for Responsible Integration in Research and Practice

Abstract

This monograph provides a comprehensive governance and implementation framework for the responsible integration of artificial intelligence (AI) in public health research and practice. Drawing on established ethical principles, Australian and international regulatory guidance, and emerging empirical evidence, the work introduces a multi-layered supervision architecture designed to ensure safety, transparency, cultural appropriateness, and epistemic integrity in AI deployment. Key concepts include a Five‑Loop Supervision Framework, mechanisms for mitigating algorithmic bias, protocols for responsible collective intelligence, and technical safeguards such as retrieval‑augmented generation (RAG) verification, privacy‑preserving infrastructures, and compliance requirements aligned with NHMRC, WHO, and EU AI Act guidelines. The monograph offers practical implementation roadmaps for Australian health institutions, including phased adoption strategies, fairness audits, stakeholder engagement models, Indigenous data governance requirements, and critical success factors for scaling AI responsibly. It supports clinicians, researchers, policymakers, evaluators, and digital health leaders in making informed, ethically grounded decisions about AI deployment while maintaining human judgement as the ultimate determinant of public health practice.

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