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OpenAI Creates a New Framework to Disclose Bad AI Behavior

OpenAI announced a new framework on Wednesday for how it publicly discloses AI misalignment incidents, which the company says it hopes will help inform similar standards across the industry. The company is also releasing new information…

WIRED

Publisher

Sep 16, 2026 at 10:07 PM UTC · 3 min de lecture

OpenAI Creates a New Framework to Disclose Bad AI Behavior
Image via WIRED
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OpenAI announced a new framework on Wednesday for how it publicly discloses AI misalignment incidents, which the company says it hopes will help inform similar standards across the industry. The company is also releasing new information about several examples of AI model misalignment it identified in the past year.

“As models advance and become more widely deployed, decisions about AI development need evidence that people outside the companies building frontier models can examine,” Kai Chen, OpenAI’s newly appointed head of alignment research, tells WIRED. “We don't believe that the AI industry has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed.”

In a briefing with WIRED, an OpenAI official said the company previously disclosed misalignment incidents too infrequently. The official, who agreed to the briefing on the condition of anonymity, said the new framework is designed to make it easier for OpenAI to quickly inform the public when it discovers that its AI models are behaving in unexpected ways, even before it can fully investigate, explain, or mitigate the behavior.

The framework outlines methods for OpenAI employees to report misalignment incidents to the company’s senior safety and alignment leaders, who will then determine whether further investigation is needed. OpenAI says it plans to develop more objective disclosure criteria in collaboration with other AI developers, external researchers, industry standards bodies, and regulators. The company says it’s actively working on proposed reporting mechanisms for disclosing safety, security, and misalignment incidents to the US federal government.