Governance of artificial intelligence: A risk and guideline-based integrative framework
A public-sector-focused AI risk taxonomy may offer APS governance practitioners a structured vocabulary for risk identification and policy cycle work.
Key points
- A 2022 academic framework proposes six AI risk categories specifically designed for public sector governance contexts.
- The taxonomy links technological, ethical, legal, social, economic, and informational risks to concrete governance guidelines.
- This is a blog summary of a three-year-old paper - useful reference material but not a new development.
Summary
The MIT AI Risk Repository has spotlighted a 2022 paper by Wirtz, Weyerer, and Kehl published in Government Information Quarterly, which presents a six-category AI risk taxonomy tailored to public sector organisations. The taxonomy covers technological, informational, economic, social, ethical, and legal/regulatory risks, and links each category to governance guidelines through a four-layer conceptual model and a seven-stage policy cycle. The framework is specifically designed to address public sector concerns such as democratic legitimacy, citizen trust, and public value creation. The item itself is a blog summary rather than new research.
Implications for Australian agencies
- Consider APS governance and risk teams may want to review the original paper to assess whether its six-category taxonomy complements existing Australian frameworks such as the Policy for the Responsible Use of AI in Government.
- Monitor The MIT AI Risk Repository's ongoing series spotlighting public-sector-focused frameworks may be worth tracking as a curated reference for comparative risk taxonomy work.
Implications are AI-generated. Starting points, not advice.
"Governance of artificial intelligence: A risk and guideline-based integrative framework" Source: MIT AI Risk Repository – Blog Published: 16 July 2025 URL: https://airisk.mit.edu/blog/governance-of-artificial-intelligence-a-risk-and-guideline-based-integrative-framework The MIT AI Risk Repository has spotlighted a 2022 paper by Wirtz, Weyerer, and Kehl published in Government Information Quarterly, which presents a six-category AI risk taxonomy tailored to public sector organisations. The taxonomy covers technological, informational, economic, social, ethical, and legal/regulatory risks, and links each category to governance guidelines through a four-layer conceptual model and a seven-stage policy cycle. The framework is specifically designed to address public sector concerns such as democratic legitimacy, citizen trust, and public value creation. The item itself is a blog summary rather than new research. Implications for Australian agencies: - [Consider] APS governance and risk teams may want to review the original paper to assess whether its six-category taxonomy complements existing Australian frameworks such as the Policy for the Responsible Use of AI in Government. - [Monitor] The MIT AI Risk Repository's ongoing series spotlighting public-sector-focused frameworks may be worth tracking as a curated reference for comparative risk taxonomy work. Retrieved from SIMS, 18 May 2026.