三名被解雇的OpenAI安全研究员称，他们从未被告知自己究竟泄露了什么

Three OpenAI safety researchers who were fired deny sharing confidential information. They suspect their terminations were tied to their efforts to make AI models easier to monitor and warn that the case could discourage employees from raising safety concerns. OpenAI cited alleged policy violations. The researchers say investigators focused on their Signal chats with outside researchers, though OpenAI said Signal was not the reason for the firings. The three OpenAI safety researchers who were fired over alleged leaks are telling their side of the story. Tomek Korbak, Mikita Balesni, and Jasmine Wang deny sharing confidential information, question the official reasoning behind their termination, and suspect a connection to their advocacy for more transparent AI systems. OpenAI dismissed all three after an internal investigation into alleged violations of its policies on handling sensitive information. Each of them had spoken publicly about AI risks before being let go. In interviews with the Wall Street Journal , the researchers now dispute that account. OpenAI told the Journal that the firings had nothing to do with safety concerns the researchers had raised. But the three say they were never told in writing which information they supposedly mishandled. They also worry the case could discourage independent safety auditors from working with AI companies altogether. Ad The Journal's reporting sheds light on what led to the confrontation. OpenAI's security team suspected the three of sharing details about the company's internal model architecture with an external safety researcher and asked them to unlock their personal phones. On those devices, the team found Signal chats with disappearing messages enabled. A week later, all three were fired at the same time. OpenAI said Signal was not an approved communication tool but insisted it was not the reason for the terminations. Korbak counters that disappearing messages are a routine security practice across Silicon Valley. Ad The dispute centers on a technical question with major consequences. Should AI companies let outsiders inspect how their models think? Reasoning models can record the intermediate steps of their problem-solving process on an internal scratchpad known as the chain of thought . Companies and safety researchers rely on these traces to understand how models arrive at their decisions. In a 2025 paper, Balesni, Korbak, and Wang joined leading researchers from several AI labs in calling for continued access to this capability. The issue grew more urgent over the summer, when employees at AI companies began discussing models that think longer but write down fewer intermediate steps . Balesni pushed back internally by sharing a related proposal from Ryan Greenblatt, then chief scientist at Redwood Research. Ad Korbak, too, was in regular contact with Greenblatt. The two communicated over Slack and Signal while working together on the analysis of a high-profile incident—the attack by OpenAI agents on Hugging Face—for which Greenblatt had been hired by METR to conduct an independent investigation . That cooperation became a liability after The Information reported on September 1 that OpenAI's new model Astra was more capable but revealed less of its reasoning process. OpenAI chief scientist Jakub Pachocki dismissed the report as muddled at the time on X, even though he himself had warned of an industry-wide race toward models that can no longer be monitored . Ad A few weeks later, OpenAI launched an internal leak investigation, according to the Journal. Balesni says investigators named Greenblatt as the suspected source and demanded to see the Signal chats with him. Greenblatt denies passing confidential information to journalists. Ad