AI Risk Categorization Decoded $($AIR $2024)$: Summary

This paper introduces the AI Risk Taxonomy $($AIR $2024),$ a comprehensive framework for categorizing risks associated with generative AI models and systems. It addresses the need for a unified language for evaluating AI safety by drawing on regulations and policies from governments and companies around the world.

Here's a breakdown of the key points:

Motivation: Different sectors $($government$,$ industry$)$ use diverse terminology for AI risks, hindering communication and collaboration. AIR $2024$ aims to bridge this gap.

Methodology: Researchers analyzed policies from eight government bodies $($EU$,$ US$,$ China$)$ and $16$ companies to identify a total of $314$ unique risk categories.

Structure: The taxonomy is hierarchical, with four levels:

Level $1$: Broad categories $($System & Operational, Content Safety, Societal, Legal & Rights$)$

Level $2$: More specific categories $($e$.$g$.,$ Operational Misuses under System & Operational$)$

Level $3$: Even more granular breakdowns $($e$.$g$.,$ Automated Decision$-$Making under Operational Misuses$)$

Level $4$: Most detailed risk categories explicitly mentioned in policies $($e$.$g$.,$ Financing eligibility$/$Creditworthiness under Automated Decision$-$Making$)$

Benefits of AIR $2024$:

Standardized Framework: Enables consistent AI safety evaluations across regions and sectors$.$

Insights into Corporate Risk Management: Reveals how companies prioritize and perceive AI risks.

Comparative Analysis of Regulations: Helps understand how different governments approach AI governance.

Improved Communication: Provides a common language for policymakers, researchers, and industry leaders.

Safer AI Development and Deployment: Guides efforts to mitigate risks and promote responsible AI practices.

The paper also discusses challenges encountered during taxonomy development, such as the use of varying terminology in different policies. It emphasizes the importance of ongoing updates as regulations and company policies evolve.

Overall, AIR $2024$ is a valuable resource for anyone involved in the development, deployment, or governance of generative AI$.$ It promotes a shared understanding of AI risks and facilitates collaboration towards safer and more beneficial AI applications. can analyze scholastic the images of the paper?Figure $1$: Overview of the AI risk taxonomy derived from $24$ policy and regulatory documents,

encompassing $314$ unique risk categories. Charts on the right$-$hand side map to major AI regulations.