Search papers, labs, and topics across Lattice.
This paper addresses the critical oversight in safety analysis of large language models (LLMs) by applying Systems-Theoretic Process Analysis (STPA) to the LLMs themselves, introducing a method called Constitutional Meta-STPA. The authors derive a governance constitution comprising 21 Tool Principles and 8 Meta-Safety Principles, demonstrating that the tool can self-validate its safety framework through a closed-loop analysis. Key findings reveal that a stronger ensemble model recovers a majority of the principles, indicating that the meta-analysis is limited by model capabilities rather than the constitution itself.
Self-analysis of LLMs reveals that a stronger model ensemble can recover 86% of safety principles, challenging assumptions about tool reliability in safety-critical applications.
Large language models (LLMs) are increasingly trusted to draft the artifacts of safety analysis such as, losses, hazards, Unsafe Control Actions (UCAs), and safety constraints, inside rigorous processes such as Systems-Theoretic Process Analysis (STPA). Yet a blind spot runs through this fast-growing literature: every system gets analysed except the LLM-assisted tool doing the analysing, which is itself a safety-relevant system that can hallucinate standards, emit unverifiable constraints, and leave no audit trail from prompt to artifact. We take seriously the question the field has skipped -- {who analyses the analyser?} and answer it by turning STPA on the tool itself. We present \{Constitutional Meta-STPA}, an LLM-assisted STPA tool built around a closed loop: the tool runs a {meta-STPA} of the class of AI-assisted safety tools and {derives} rather than asserts, its governance constitution from the resulting loss$\to$hazard$\to$UCA$\to$constraint chain, yielding a published constitution of $21$ Tool Principles and $8$ Meta-Safety Principles, each bound to a code enforcement point. We formalise the measured object as a constitution-marginal coverage operator over a principle set $P$ ($|P|{=}29$) with a soundness lemma that isolates coverage from model and scanner, and report four findings. {(i)~Self-derivation:} a frontier ensemble ({claude-opus-4.8}${+}${claude-sonnet-4}) recovers $18/21$ canonical and all $8/8$ governance principles from the tool's own design, while a weaker pair recovers $12/21$ and $3/8$, so the meta layer is model-limited, not constitution-limited, and the same $8/8$ re-emerge from a second, independently authored tool.
