Cover Image

Measurement challenges in AI catastrophic risk governance and safety frameworks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Kasirzadeh, Atoosa
Format:	Preprint
Published:	2024
Subjects:	Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Two Types of AI Existential Risk: Decisive and Accumulative
by: Kasirzadeh, Atoosa
Published: (2024)

AI Safety for Everyone
by: Gyevnar, Balint, et al.
Published: (2025)

Bridging the Gap in the Responsible AI Divides
by: Gyevnár, Bálint, et al.
Published: (2026)

Characterizing AI Agents for Alignment and Governance
by: Kasirzadeh, Atoosa, et al.
Published: (2025)

AI, Digital Platforms, and the New Systemic Risk
by: Hacker, Philipp, et al.
Published: (2025)

Explanation Hacking: The perils of algorithmic recourse
by: Sullivan, Emily, et al.
Published: (2024)

A Taxonomy of Systemic Risks from General-Purpose AI
by: Uuk, Risto, et al.
Published: (2024)

What AI evaluations for preventing catastrophic risks can and cannot do
by: Barnett, Peter, et al.
Published: (2024)

Against racing to AGI: Cooperation, deterrence, and catastrophic risks
by: Dung, Leonard, et al.
Published: (2025)

Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models
by: Ungless, Eddie L., et al.
Published: (2024)

Third-party compliance reviews for frontier AI safety frameworks
by: Homewood, Aidan, et al.
Published: (2025)

A safety risk assessment framework for children's online safety based on a novel safety weakness assessment approach
by: Ta, Vinh-Thong
Published: (2024)

Affirmative safety: An approach to risk management for high-risk AI
by: Wasil, Akash R., et al.
Published: (2024)

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
by: Tang, Zeyu, et al.
Published: (2025)

Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work
by: Ovadya, Aviv, et al.
Published: (2024)

Small models, big threats: Characterizing safety challenges from low-compute AI models
by: Puri, Prateek
Published: (2026)

Legal Alignment for Safe and Ethical AI
by: Kolt, Noam, et al.
Published: (2026)

US-China perspectives on extreme AI risks and global governance
by: Wasil, Akash, et al.
Published: (2024)

Epistemic Injustice in Generative AI
by: Kay, Jackie, et al.
Published: (2024)

Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning
by: Smart, Andrew, et al.
Published: (2024)

A five-layer framework for AI governance: integrating regulation, standards, and certification
by: Agarwal, Avinash, et al.
Published: (2025)

Cross-cultural value alignment frameworks for responsible AI governance: Evidence from China-West comparative analysis
by: Liu, Haijiang, et al.
Published: (2025)

Framing metaverse identity: A multidimensional framework for governing digital selves
by: Yang, Liang, et al.
Published: (2024)

AI for bureaucratic productivity: Measuring the potential of AI to help automate 143 million UK government transactions
by: Straub, Vincent J., et al.
Published: (2024)

Dynamic safety cases for frontier AI
by: Cârlan, Carmen, et al.
Published: (2024)

Lessons from complexity theory for AI governance
by: Kolt, Noam, et al.
Published: (2025)

Artificial Intelligence in Governance, Risk and Compliance: Results of a study on potentials for the application of artificial intelligence (AI) in governance, risk and compliance (GRC)
by: Ponick, Eva, et al.
Published: (2022)

Assessing confidence in frontier AI safety cases
by: Barrett, Stephen, et al.
Published: (2025)

The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
by: Coggins, Sam, et al.
Published: (2025)

The More You Automate, the Less You See: Hidden Pitfalls of AI Scientist Systems
by: Luo, Ziming, et al.
Published: (2025)

Towards an AI Observatory for the Nuclear Sector: A tool for anticipatory governance
by: Verma, Aditi, et al.
Published: (2025)

Operationalising AI governance through ethics-based auditing: An industry case study
by: Mokander, Jakob, et al.
Published: (2024)

Fairness in AI: challenges in bridging the gap between algorithms and law
by: Giannopoulos, Giorgos, et al.
Published: (2024)

AI Emergency Preparedness: Examining the federal government's ability to detect and respond to AI-related national security threats
by: Wasil, Akash, et al.
Published: (2024)

Generative AI and the problem of existential risk
by: Webb, Lynette
Published: (2024)

A risk model and analysis method for the psychological safety of human and autonomous vehicles interaction
by: Sirgabsou, Yandika, et al.
Published: (2024)

A pragmatic classification framework for AI incident monitoring
by: Mengesha, Isaak, et al.
Published: (2026)

Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance
by: Corrêa, Nicholas Kluge, et al.
Published: (2022)

Domestic frontier AI regulation, an IAEA for AI, an NPT for AI, and a US-led Allied Public-Private Partnership for AI: Four institutions for governing and developing frontier AI
by: Belfield, Haydn
Published: (2025)

The science and practice of proportionality in AI risk evaluations
by: Mougan, Carlos, et al.
Published: (2026)