Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review
Contextualises AI risk categorisation approaches used in the MIT AI Risk Repository — a reference some APS agencies may draw on for framework development.
Key points
- MIT AI Risk Repository spotlights a 2016 literature review categorising AI ethical risks along three axes.
- The framework uses PEST analysis to propose management strategies including ethics committees and AI security measures.
- The source paper is nearly a decade old; field has advanced significantly since its publication.
Implications for Australian agencies
- Monitor Agencies building AI risk frameworks may want to monitor the MIT AI Risk Repository as a whole, rather than engaging with individual older spotlighted papers.
Implications are AI-generated. Starting points, not advice — see methodology for how they're framed.
View original source
Copied.
"Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review"
Source: MIT AI Risk Repository – Blog
Published: 2 January 2025
URL: https://airisk.mit.edu/blog/managing-the-ethical-and-risk-implications-of-rapid-advances-in-artificial-intelligence-a-literature-review
The MIT AI Risk Repository blog spotlights one of the frameworks underpinning its repository: a 2016 conference paper by Meek et al. that applies thematic and PEST analysis to categorise AI ethical risks across three axes — type of AI, focus area, and risk severity. The paper proposes management strategies such as establishing ethics committees and embedding ethics in technology management. While the repository itself is a live and useful reference for APS risk and governance practitioners, this particular spotlight concerns a dated paper whose prescriptions have since been substantially superseded by more recent frameworks and standards.
Implications for Australian agencies:
- [Monitor] Agencies building AI risk frameworks may want to monitor the MIT AI Risk Repository as a whole, rather than engaging with individual older spotlighted papers.
Retrieved from SIMS, 18 July 2026.