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- Machine learning in medicine: Addressing ethical challenges
- Ethics in healthcare AI: how should the industry prepare?
- Building the case for actionable ethics in digital health research supported by artificial intelligence
- Intro to AI Ethics
- The Best Books on Ethics for Artificial Intelligence recommended by Paula Boddington
- AI effects on law, ethics, and society
- Artificial Intelligence in Healthcare – The Need for Ethics (TEDx)
- How to keep human bias out of AI (TEDx)
- Preventing disasters: Why safety is the foundation of medical machine learning
- AI: Ethics, Bias, and Trust (Coursera)
Principles and Guidelines: Health
- World Health Organisation guidance on Ethics & Governance of Artificial Intelligence for Health
- RANZCR Ethical Principles for AI in Medicine – Consultation (New Zealand)
- HDEC Health information and data use – guidance (New Zealand)
- Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril
Principles and Guidelines: Other areas
- Ethically aligned design, published by the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
- EU Ethics Guidelines for Trustworthy Artificial Intelligence (AI) (EU)
- High-Level Expert Group on Artificial Intelligence
- Artificial Intelligence Australia’s Ethics Framework
- US White House Principles for Guidance for Regulation of Artificial Intelligence Applications
Data Sovereignty
- Te Mana Raraunga – Māori Data Sovereignty Network (New Zealand)
- Indigenous Data Sovereignty – Toward an agenda (Australia)
New Zealand-specific
- Algorithm Charter for Aotearoa New Zealand
- The NZ Government Social Wellbeing Agency’s Data Protection & Use Policy
- Ethics of NZ Public Health System data use
- Health data research in New Zealand: updating the ethical governance framework