Australia’s AI Ethics Principles
Australia's AI Ethics Principles provide voluntary guidance for businesses and governments to responsibly design, develop, and implement artificial intelligence systems. The framework consists of eight core principles addressing human, societal, and environmental wellbeing, human-centred values, fairness, privacy and security, reliability and safety, transparency and explainability, contestability, and accountability. These principles aim to ensure AI is safe, secure, and reliable while achieving fairer outcomes for all Australians.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Businesses and governments designing, developing, or implementing AI systems should read this to align with responsible AI practices.
What the document contains
The document outlines eight core ethical principles for the design, development, and implementation of AI systems. It covers broad societal goals, human rights alignment, fairness, security, reliability, transparency, contestability, and accountability.
The text does not contain specific legislative penalties, binding regulatory enforcement mechanisms, or technical compliance definitions.
- AI systems should benefit individuals, society, and the environment throughout their lifecycle.
- Systems must respect human rights, diversity, and individual autonomy.
- AI applications should be inclusive, accessible, and free from unfair discrimination.
- Organizations must ensure data protection, robust security, and reliable operation according to intended purposes.
- Mechanisms must be established to provide transparency, explainability, and ways for affected people to contest AI outcomes.
· Human, societal and environmental wellbeing · Human-centred values · Fairness · Privacy protection and security · Reliability and safety · Transparency and explainability · Contestability · Accountability
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.
Accountability
screening score · 2026-10-24
Fairness
4/5Non-discrimination and equitable treatment
Measures should be taken to ensure the AI produced decisions are compliant with anti‐discrimination laws.
Fairness
screening score · 2026-10-24
Human Dignity
4/5Respect for the inherent worth of persons
AI systems should enable an equitable and democratic society by respecting, protecting and promoting human rights, enabling diversity, respecting human freedom and the autonomy of individuals
Human-centred values
screening score · 2026-10-24
Human Oversight
4/5Humans remain in control of consequential decisions
They must consider the appropriate level of human control or oversight for the particular AI system or use case.
Accountability
screening score · 2026-10-24
Privacy
4/5Protection of personal data and private life
This includes ensuring proper data governance, and management, for all data used and generated by the AI system throughout its lifecycle.
Privacy protection and security
screening score · 2026-10-24
Transparency
4/5Openness about how AI systems work and are used
There should be transparency and responsible disclosure so people can understand when they are being significantly impacted by AI
Transparency and explainability
screening score · 2026-10-24
Enforcement
1/5Consequences and compliance mechanisms with real force
The application of legal principles regarding accountability for AI systems is still developing.
Accountability
screening score · 2026-10-24
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
Those impacts, both positive and negative, should be accounted for throughout the AI system’s lifecycle, including impacts outside the organisation.
Human, social and environmental wellbeing
screening score · 2026-10-24