Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review
A structured AI risk taxonomy with management strategies - useful context for APS ethics frameworks, though age limits direct applicability.
Key points
- MIT AI Risk Repository spotlights a 2016 literature review categorising AI ethical risks across three analytical axes.
- The framework uses PEST analysis to structure AI risk and proposes strategies like ethics committees and embedded ethics processes.
- The source paper is nearly a decade old; field has advanced significantly since, limiting direct applicability for current APS use.
Summary
The MIT AI Risk Repository has highlighted a 2016 conference paper by Meek et al. that applies thematic and PEST analysis to categorise AI ethical risks across dimensions of AI type, focus area, and risk severity. The framework proposes actionable strategies including establishing ethics committees and embedding ethics into technology management. While the MIT AI Risk Repository itself is a useful reference for APS risk and governance practitioners, this particular paper predates most contemporary AI governance developments and should be treated as background context rather than current guidance.
Implications for Australian agencies
- Monitor APS practitioners building AI risk taxonomies may want to monitor the MIT AI Risk Repository more broadly, as it consolidates multiple frameworks that could inform agency-level risk assessment approaches.
Implications are AI-generated. Starting points, not advice.
"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 has highlighted a 2016 conference paper by Meek et al. that applies thematic and PEST analysis to categorise AI ethical risks across dimensions of AI type, focus area, and risk severity. The framework proposes actionable strategies including establishing ethics committees and embedding ethics into technology management. While the MIT AI Risk Repository itself is a useful reference for APS risk and governance practitioners, this particular paper predates most contemporary AI governance developments and should be treated as background context rather than current guidance. Implications for Australian agencies: - [Monitor] APS practitioners building AI risk taxonomies may want to monitor the MIT AI Risk Repository more broadly, as it consolidates multiple frameworks that could inform agency-level risk assessment approaches. Retrieved from SIMS, 18 May 2026.