From nuclear testing moratoriums to AI safety thresholds

Over 33 years ago, the US conducted its final nuclear test - transitioning to a science-based Stockpile Stewardship Program that maintains civilization-ending arsenals through simulations alone, never testing them again.​​ New AI safety research has found frontier models achieving 70% performance on complex software engineering tasks and demonstrating potential for weaponised capabilities - prompting developers to deploy unprecedented safety controls not because they've definitively crossed danger thresholds, but because they cannot rule out crossing them.​​ Whilst nuclear warheads and AI systems are very different - one frozen-in-time physics, the other evolving from under 10% to 70% capability in under two years - we can draw interesting parallels with regard to governing powerful technologies through computational assessment rather than direct testing when the risks of empirical validation become unacceptable.​​ Will your organisation wait for evidence of actual harm before implementing enhanced AI controls or will you trigger safeguards when capability thresholds are reached? Profiled research: International AI Safety Report 2025: First Key Update: https://doi.org/10.48550/arXiv.2510.13653; Detecting and Reducing Scheming in AI Models: https://openai.com/index/detecting-and-reducing-scheming-in-ai-models/; LLM Jailbreak Detection for (Almost) Free: https://doi.org/10.48550/arXiv.2509.14558; InvThink: Towards AI Safety via Inverse Reasoning: https://doi.org/10.48550/arXiv.2510.01569; AI Red-Teaming Design: Threat Models and Tools: https://cset.georgetown.edu/article/ai-red-teaming-design-threat-models-and-tools/

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