# Safety Cases: A Scalable Approach to Frontier AI Safety

arXiv: https://arxiv.org/abs/2503.04744 · HTML: https://mlsanity.com/paper/2503.04744/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 5 references that are in the map.
- First posted on arXiv 5 Feb 2025.

## Builds on (most cited first, 3 of 3)

- [AI Control: Improving Safety Despite Intentional Subversion](https://mlsanity.com/paper/2312.06942/) (2023)
- [AI Sandbagging: Language Models can Strategically Underperform on Evaluations](https://mlsanity.com/paper/2406.07358/) (2024)
- [The rising costs of training frontier AI models](https://mlsanity.com/paper/2405.21015/) (2024)

## Built on by (most cited first, 8 of 8)

- [When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors](https://mlsanity.com/paper/2507.05246/) (2025)
- [How to evaluate control measures for LLM agents? A trajectory from today to superintelligence](https://mlsanity.com/paper/2504.05259/) (2025)
- [An alignment safety case sketch based on debate](https://mlsanity.com/paper/2505.03989/) (2025)
- [STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reports](https://mlsanity.com/paper/2508.09853/) (2025)
- [When Do LLM Preferences Predict Downstream Behavior?](https://mlsanity.com/paper/2602.18971/) (2026)
- [Systematic Hazard Analysis for Frontier AI using STPA](https://mlsanity.com/paper/2506.01782/) (2025)
- [Clear, Compelling Arguments: Rethinking the Foundations of Frontier AI Safety Cases](https://mlsanity.com/paper/2603.08760/) (2026)
- [Questionnaire Responses Do not Capture the Safety of AI Agents](https://mlsanity.com/paper/2603.14417/) (2026)

## Abstract (arXiv)

Safety cases - clear, assessable arguments for the safety of a system in a given context - are a widely-used technique across various industries for showing a decision-maker (e.g. boards, customers, third parties) that a system is safe. In this paper, we cover how and why frontier AI developers might also want to use safety cases. We then argue that writing and reviewing safety cases would substantially assist in the fulfilment of many of the Frontier AI Safety Commitments. Finally, we outline open research questions on the methodology, implementation, and technical details of safety cases.