Navigating the Landscape of AI Ethics and Responsibility
Provides a structured taxonomy of AI ethics risks that APS governance teams could use to cross-check coverage in existing risk frameworks.
Key points
- A 2023 academic framework clusters AI ethics and responsibility issues into six groups via systematic literature review.
- The six clusters — broken systems, hallucinations, IP violations, privacy, malicious use, and environmental harm — map closely to APS AI risk categories.
- This is a blog summary of an existing academic paper; it is secondary source material with limited new content.
Summary
MIT's AI Risk Repository blog summarises a 2023 academic paper by Cunha and Estima that uses systematic literature review and real-world AI incident analysis to produce a six-cluster framework for AI ethics and responsibility issues. The clusters cover algorithm failures and bias, hallucinations, intellectual property violations, privacy breaches, malicious use enablement, and environmental and socioeconomic harms. The framework recommends that ethics and responsibility be addressed across five dimensions: Research, Education, Development, Operation, and Business Model. The content is a secondary summary of a pre-existing paper rather than new findings.
Implications for Australian agencies
- Consider Agencies reviewing or refreshing AI risk frameworks could cross-check their existing risk taxonomy against the six clusters to identify any coverage gaps.
- Monitor APS staff tracking the MIT AI Risk Repository may want to note this as background context when the Repository is cited in policy or vendor risk discussions.
Implications are AI-generated. Starting points, not advice.
"Navigating the Landscape of AI Ethics and Responsibility" Source: MIT AI Risk Repository – Blog Published: 11 September 2024 URL: https://airisk.mit.edu/blog/navigating-the-landscape-of-ai-ethics-and-responsibility MIT's AI Risk Repository blog summarises a 2023 academic paper by Cunha and Estima that uses systematic literature review and real-world AI incident analysis to produce a six-cluster framework for AI ethics and responsibility issues. The clusters cover algorithm failures and bias, hallucinations, intellectual property violations, privacy breaches, malicious use enablement, and environmental and socioeconomic harms. The framework recommends that ethics and responsibility be addressed across five dimensions: Research, Education, Development, Operation, and Business Model. The content is a secondary summary of a pre-existing paper rather than new findings. Implications for Australian agencies: - [Consider] Agencies reviewing or refreshing AI risk frameworks could cross-check their existing risk taxonomy against the six clusters to identify any coverage gaps. - [Monitor] APS staff tracking the MIT AI Risk Repository may want to note this as background context when the Repository is cited in policy or vendor risk discussions. Retrieved from SIMS, 18 May 2026.