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OpenAI stands firm on firing three safety researchers

OpenAI stands firm on firing three safety researchers

In a post on X on Friday, OpenAI said Jasmine Wang, Tomek Korbak and Mikita Balesni were dismissed for violating "clear policies on handling sensitive information," and insisted the decision was not about their AI safety concerns.

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Context & Analysis

OpenAI's public defense of the firings marks a rare direct confrontation between the company and former employees who worked on safety. The company says the researchers violated information-handling policies, while the three say they were punished for raising safety concerns and acted in line with OpenAI's mission and the working norms of the time.

The dispute follows a year of high-profile breaches, most notably OpenAI's hack of Hugging Face, which the company cites as context for why staff are worried about frontier-system safety. Some employees are now calling on AI companies to slow down and do more to guard against the consequences of building self-improving systems — a demand that sits awkwardly beside OpenAI's insistence that this particular dismissal was about policy breaches, not safety advocacy.

FAQ
Why did OpenAI fire the researchers?
OpenAI said Jasmine Wang, Tomek Korbak and Mikita Balesni violated "clear policies on handling sensitive information," and that an internal investigation found breaches "beyond what's outlined in the letter." OpenAI did not provide details of those breaches.
How did the researchers respond?
They published an open letter on Thursday urging OpenAI to be more transparent about the decision. In it and in social media posts, they said they believed they were fired for raising safety concerns and had "acted in line with OpenAI's mission and within the working norms of the time."
What does this say about safety concerns inside AI companies?
The safety of frontier systems has become an increasing concern for staff inside AI companies following a series of high profile breaches this year, most notably OpenAI's hack of Hugging Face. Many staff are now calling for companies to slow down and do more to guard against the potential consequences of building self-improving systems.

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