mlsanityData to 14 Oct 2026

Safety cases for frontier AI

arXiv 2410.21572 ↗First posted 28 Oct 2024cs.CYcited by 18

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Abstract (arXiv)

As frontier artificial intelligence (AI) systems become more capable, it becomes more important that developers can explain why their systems are sufficiently safe. One way to do so is via safety cases: reports that make a structured argument, supported by evidence, that a system is safe enough in a given operational context. Safety cases are already common in other safety-critical industries such as aviation and nuclear power. In this paper, we explain why they may also be a useful tool in frontier AI governance, both in industry self-regulation and government regulation. We then discuss the practicalities of safety cases, outlining how to produce a frontier AI safety case and discussing what still needs to happen before safety cases can substantially inform decisions.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Oct 2024.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 9; 2026: 7.

18 papers.

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  1. 2025Levels of Autonomy for AI Agentscited by 48
  2. 2025Evaluating Frontier Models for Stealth and Situational Awarenesscited by 37
  3. 2024Evaluation-Driven Development and Operations of LLM Agents: A Process Model and Reference Architecturecited by 11
  4. 2025The Singapore Consensus on Global AI Safety Research Prioritiescited by 10
  5. 2025STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reportscited by 10
  6. 2025Manipulation Attacks by Misaligned AI: Risk Analysis and Safety Case Frameworkcited by 5
  7. 2026Tool Use Enables Undetectable Steganography in Multi-Agent LLM Systemscited by 5
  8. 2025International Agreements on AI Safety: Review and Recommendations for a Conditional AI Safety Treatycited by 4
  9. 2025An Example Safety Case for Safeguards Against Misusecited by 4
  10. 2025Misalignment or misuse? The AGI alignment tradeoffcited by 4
  11. 2026LURE: Live-Usage Replay Evaluations for Reducing Evaluation Awarenesscited by 4
  12. 2025Against racing to AGI: Cooperation, deterrence, and catastrophic riskscited by 2
6 more
  1. 2026Position: Behavioural Assurance Cannot Verify the Safety Claims Governance Now Demandscited by 2
  2. 2024Quantifying detection rates for dangerous capabilities: a theoretical model of dangerous capability evaluationscited by 1
  3. 2026Open Problems in AI Incident Governancecited by 1
  4. 2026Incentive Aware AI Regulations: A Credal Characterisationcited by 0
  5. 2026Questionnaire Responses Do not Capture the Safety of AI Agentscited by 0
  6. 2026Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speechcited by 0