A framework for ethical AI at the United Nations
A catalogued AI risk taxonomy from a UN context offers comparative value for agencies building or auditing their own risk registers - though more current Australian frameworks exist.
Key points
- A 2021 UN-focused ethical AI framework identifies 13 risk categories from incompetence to lethal autonomous weapons.
- The MIT AI Risk Repository has catalogued this framework as one of six reference frameworks for AI risk taxonomy work.
- The paper is three years old and UN-scoped; APS practitioners likely have more current and jurisdiction-specific references available.
Summary
The MIT AI Risk Repository has summarised Lambert Hogenhout's 2021 paper proposing an ethical AI framework for the United Nations. The framework enumerates 13 AI risk categories - ranging from bias and lack of transparency through to lethal autonomous weapons, manipulation, and exclusion - and argues for practical assessment tools to ensure AI development aligns with human ethical values. The paper explores multiple ethical frameworks and proposes a structured path for UN adoption. As a 2021 arXiv preprint contextualised for UN institutions, it predates more recent Australian and international risk frameworks but may still inform comparative taxonomy work.
Implications for Australian agencies
- Monitor Agencies developing AI risk registers may want to note this taxonomy as a comparative reference, though Australian-specific frameworks such as the DISR responsible AI principles and NIST AI RMF are likely more immediately applicable.
Implications are AI-generated. Starting points, not advice.
"A framework for ethical AI at the United Nations" Source: MIT AI Risk Repository – Blog Published: 2 October 2024 URL: https://airisk.mit.edu/blog/a-framework-for-ethical-ai-at-the-united-nations-2 The MIT AI Risk Repository has summarised Lambert Hogenhout's 2021 paper proposing an ethical AI framework for the United Nations. The framework enumerates 13 AI risk categories - ranging from bias and lack of transparency through to lethal autonomous weapons, manipulation, and exclusion - and argues for practical assessment tools to ensure AI development aligns with human ethical values. The paper explores multiple ethical frameworks and proposes a structured path for UN adoption. As a 2021 arXiv preprint contextualised for UN institutions, it predates more recent Australian and international risk frameworks but may still inform comparative taxonomy work. Implications for Australian agencies: - [Monitor] Agencies developing AI risk registers may want to note this taxonomy as a comparative reference, though Australian-specific frameworks such as the DISR responsible AI principles and NIST AI RMF are likely more immediately applicable. Retrieved from SIMS, 18 May 2026.