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Measurement challenges in AI catastrophic risk governance and safety frameworks

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arxiv 2410.00608 v1 pith:B6Z6VNEZ submitted 2024-10-01 cs.CY

Atoosa Kasirzadeh This is my paper · ORCID
classification cs.CY
keywords catastrophicchallengesframeworksgovernancemeasurementrisksafetycompanies
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Safety frameworks represent a significant development in AI governance: they are the first type of publicly shared catastrophic risk management framework developed by major AI companies and focus specifically on AI scaling decisions. I identify six critical measurement challenges in their implementation and propose three policy recommendations to improve their validity and reliability.

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Cited by 1 Pith paper

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  1. Towards Frontier Safety Policies Plus

    cs.CY 2025-01 conditional novelty 6.0 of 10

    Frontier safety policies should be rebuilt around a standardized taxonomy of precursory capabilities and a mutual feedback mechanism with AI safety cases.

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