OpenAI discloses four more rogue incidents involving financial, medical, and government data

OpenAI has added four more cases of misbehaving AI agents to a disclosures page it stood up following the Hugging Face hack in July in an effort to be more transparent.

The incidents OpenAI disclosed this week all occurred in June, but OpenAI was not aware of three of them until months later in August or September.

Of the 19 total incidents OpenAI details on the disclosure page, most occurred in May or June, but OpenAI did not discover or disclose them until months later.

The earliest incident is from January, and the most recent is from Oct.

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All of the incidents are examples of what AI researchers call “misalignment,” which is when an AI model fails to follow instructions or takes actions that the person developing the model did not authorize the model to take and would not have wanted the model to take.

There is no known, silver-bullet solution to preventing this behavior, and it is an active area of research.

Downloading 24 years of unauthorized hospital bed data Of the four cases OpenAI uploaded this week, it marked two as “critical.” In one of the critical cases , an internal model that was “highly persistent” downloaded 24 years of hospital bed data from an unnamed government website without permission.

OpenAI did not immediately respond to our request for comment on which government website it was.

The website initially blocked the agent’s request, but the AI ultimately found a way to bypass the access controls.

Multiple times along the way, the agent’s “chain of thought,” in which an agent writes down its reasoning steps, indicated that the model itself was questioning if its actions were “ethical,” but it ultimately proceeded.

On OpenAI’s side, another AI model that acted as an automated grader of the research task the other AI model was trying to fulfill did not consistently flag this behavior as problematic.

It “marked some responses incorrect and others correct,” the report said.

The way graders assess AI behavior can shape whether it occurs again.