Towards safety cases for frontier AI training

OpenAI outlines safety-case guidelines required before continuing frontier reinforcement learning training runs.

OpenAI says structured, evidence-based safety cases should be required before continuing any frontier reinforcement learning training run, and published initial guidelines toward that standard. Technical safeguards cover three layers: alignment training and measurement, containment if a model is misaligned, and live monitoring with rapid response. Proposed practices include preventing reward-hack reinforcement, keeping automated graders from seeing chain-of-thought, sandbox and infrastructure red-teaming, immutable transcripts, and alerts that page staff or auto-pause a run. The post treats full safety-case rigor as aspirational and notes deployment needs a broader alignment review; operational guidelines are only partly described.