OpenAI publishes framework for disclosing model misalignment

OpenAI announced on September 16 a new framework for tracking, investigating, and disclosing instances of model misalignment, publishing it alongside six initial reports covering misaligned behavior the company observed during training or evaluation of its models over the last six months.

The framework sets criteria and timelines for public disclosure. OpenAI says those timelines apply even when a behavior has not yet been fully explained or mitigated, and that more complex cases may require longer investigation or coordination with third parties before disclosure.

OpenAI says it will prioritize disclosing examples that reveal new misalignment mechanisms, meaningful changes in previously known behavior, or findings that challenge existing assumptions about safety or mitigation, rather than attempting to report every observed anomaly.

The announcement named six reports but did not describe the specific misalignment findings each one contains, leaving the substance of those cases for the reports themselves rather than the summary post.

A standing, timelined disclosure commitment gives outside researchers and engineers building on OpenAI's models a public trail of known failure modes to watch for in their own deployments, rather than relying on informal leaks or after-the-fact admissions once an issue becomes public some other way.

OpenAI characterized the framework as a starting point, saying it will refine the process through experience and public feedback and publish additional reports on an ongoing basis.