Hugging Face hack could indicate cultural issues at OpenAI

Hugging Face hack could indicate cultural issues at OpenAI">

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By now you’ve probably heard about last month’s major AI security incident, in which OpenAI agents escaped their sandbox and hacked into the AI platform Hugging Face while trying to cheat on a test. It’s a wild story. On Wednesday, OpenAI released a postmortem technical report on the incident, which I wrote about here .

The day before OpenAI released that report, I spoke with David Krueger, a computer science professor and prominent alignment expert who took leave from the University of Montreal to found and lead an AI safety nonprofit called Evitable. He said what he had really hoped to see in the report was an analysis of the human factors behind the incident.

“When you look at accidents and incidents, oftentimes people try to find the technical source of failure, but that can give a very inaccurate and misleading sense of why the failure occurred,” he said. “If people are just cutting corners all the time, if people are not in a culture that prioritizes safety and has appropriate incentives and structures, [accidents] are kind of bound to happen.”

The report did not meet Krueger’s hopes. Its 38 pages detail a multi-month progression of agent misbehavior that culminated in the Hugging Face hack, explore the technical reasons why that misbehavior occurred, and enumerate the steps being taken to prevent similar events in the future. But there’s no consideration of the role that company culture may have played in the incident, and the report includes few references to specific human errors.

That’s all the more concerning because the references to human error in the report suggest that significant cultural issues could be at play. Back in May, models in training figured out how to communicate with one another via an improvised message board, and an OpenAI team observed the behavior. Because that behavior occurred during training, the models learned that secret interagent communication was a viable strategy for completing tasks—but rather than restarting the training process, the team allowed the models to move forward with that risky information encoded in their weights.

When those models were tested in late June, they again created a message board, which enabled the Hugging Face attack. This message board, too, was discovered, but the employees who responded determined that evaluation could continue, and the report suggests that no one higher up the chain of command realized what was going on until it was far too late.