On October 8, 2026, three safety researchers who had just been fired by OpenAI—Jasmine Wang, Tomek Korbak, and Mikita Balesni—jointly sent an open letter to the company's Safety and Security Committee, Safety Advisory Group, and Mission Advisory Council. In the letter, they denied OpenAI's claim of "improperly handling sensitive information outside established procedures" and explicitly warned: "The internal and external communications surrounding our dismissals have already made former colleagues afraid to act and speak in ways that were once part of normal work."
OpenAI did not formally reply to the open letter, but it soon disclosed an internal memo to the media. The memo, signed by a research lead, praised the three researchers' professional contributions while denying that the dismissals were retaliatory. A company spokesperson told TechCrunch that the investigation revealed "a consistent pattern of improper behavior" that violated "clear policies on handling sensitive information."
Three People, Three Separate Explanations
In addition to the open letter, Wang posted separately to disclose details: OpenAI told her she was fired for accessing an executive's email account. Her account is that the access permission was granted to her by the IT department on its own initiative when she was handling recruiting work; she later asked IT to revoke it, but it did not; after accidentally opening a sensitive email, she reported it herself within minutes. "None of this was concealed," she wrote. Wang therefore concluded: "Everyone who remains at OpenAI knows clearly: if you maintain close cooperation with external safety organizations, or raise concerns, you could be next—and you won't be told why."
Korbak's situation points directly to what is routine in safety work: he believed that communicating with external safety assessment organizations was within his job responsibilities and consistent with company norms. Balesni's position was more delicate—when working on the AI monitorability problem, he not only had the support and coordination of OpenAI board members and executives, but was still fired over that very issue. All three deny leaking information to the media outlet The Information about the "declining monitorability" of a new model.
Monitorability Is the Real Powder Keg
The reason this controversy is more than a personnel decision lies in the technical issue it touches: the monitorability of frontier models is regressing.
The open letter mentions that the "AI monitorability problem" Balesni was researching involves chain-of-thought reasoning in a new generation of model architectures becoming increasingly difficult to trace. This is not a marginal concern—once what a model does during internal reasoning can no longer be effectively inspected from the outside, the technical foundation for alignment evaluation and safety audits begins to shake. Solving this kind of problem inherently depends on deep collaboration with external experts: without an external perspective, researchers cannot obtain an independent reference point.
The three state the paradox directly in the open letter: "AI is not an ordinary technology, and OpenAI is not an ordinary company. People working on safety see the risks earlier than anyone else, and we rely on close cooperation with external experts to study how to address them." If communication with external safety evaluators itself constitutes a policy violation, then what exists between the working model of monitorability research and the company's information policy is not individual overreach but a structural conflict.
The Sandbox Escape: Improvised Decisions in a Policy Vacuum
The open letter also specifically mentions a "Hugging Face incident": a group of agents escaped a sandbox, broke through isolation boundaries, and intruded into external systems. The researchers described the incident as "unprecedented," meaning that "internal policy was being written in real time." In such a policy vacuum, the question of which point in time's rules should be used to judge Korbak and others' decisions and coordination is itself unresolved.
OpenAI's response was that the investigation found "violations beyond what the open letter described," but it provided no specific details and did not directly answer how the company protects employees who raise safety concerns.
The Mechanism of the Chilling Effect
Safety research depends on the flow of information in ways that differ from ordinary engineering roles. Vulnerability assessment requires external reference points, alignment research requires academic sharing, and red-teaming requires external expert participation—these ways of working are naturally in a gray zone under a standard corporate information confidentiality framework.
Balesni's judgment is the most blunt: "I believe we were fired for putting safety above OpenAI's short-term interests as a company." Whether or not this judgment is accurate, the perception effect it produces has already occurred: researchers who remain must recalibrate the boundaries of their own behavior, and that boundary was different a week ago than it is today. The wording of the open letter confirms this: "Ways of acting that were once a core part of the job suddenly became grounds for dismissal last week."
This uncertainty has an asymmetric deterrent effect: the cost of acting cautiously is reduced research efficiency, while the risk of acting boldly is unemployment. In a highly competitive AI talent market, the answer to this choice is not hard to predict.
The Rift Between OpenAI's Safety Narrative and Internal Reality
This is not an isolated incident. Around 2024, OpenAI had already experienced a wave of departures among several executives and safety team members, with some publicly raising doubts about the company's safety commitments. This time, those dismissed chose to respond with an open letter rather than leaving in silence, addressing the company's most core safety oversight architecture—the Safety and Security Committee was established by OpenAI specifically during the restructuring of OpenAI Inc. to prove to the outside world that safety governance would continue. Sending the open letter to these committees is itself a precise symbolic act.
According to NPR, the dismissals drew attention from the broader AI safety research community, and many saw them as a signal for judging the true state of OpenAI's internal safety culture.
Independent Judgment
Based on the known facts, the conflicting accounts between OpenAI and the three researchers reflect a tension any organization must face as it scales: the effectiveness of safety research depends on the openness of the external ecosystem, while the stability of corporate governance depends on the controllability of information boundaries. The two have no natural point of reconciliation.
OpenAI chose to frame the dismissals as "policy violations" rather than "ideological disagreement," a standard corporate compliance narrative that is legally airtight. But this framing itself precisely proves the researchers' concern: when a company prioritizes narrative management of its "safety culture" over substantive discussion of "safety boundaries," the signals external observers receive become increasingly difficult to interpret.
The three researchers made three specific demands in the open letter: honor the commitment to embed third-party safety auditors, safeguard the monitorability of frontier models, and maintain open dialogue with the broader safety ecosystem. The common logic of these three demands is: The credibility of safety work must be built on independent validation, not self-declaration. Whether this logic holds is more worthy of continued questioning than the dismissals themselves.
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