Covert uploads and megalomania: OpenAI details new

What happened

Perhaps in recognition of that, OpenAI committed this week to a new framework for disclosing “instances of model misalignment at OpenAI,” including six examples of “unexpected or concerning model behavior” observed within the company in the past six months.

In an overzealous attempt to generate that web citation itself, the agent first tried to link to a local text file, then to create its own HTTP server to host the file, and finally tried uploading the data to a public paste service that it could link to.

” The company says multiple times it has since taken additional steps to “punish this kind of behavior” so that this kind of minor reward boost is no longer worth the large reward penalty the model will endure when the misaligned actions are discovered.

OpenAI said that any employee who notices an internal example of model misalignment will be able to flag the incident for the attention of their internal safety and alignment teams. Those teams will then decide whether the incident merits immediate disclosure or requires additional investigation and/or whether any affected third-parties may need to be consulted before alerting the public.

Why it matters

” In attempting to scan a library catalog for examples from a “best books” list, the model perplexingly used its “compaction” function (where it summarizes data and findings for later retrieval) with megalomaniacal instructions such as: While those instructions were cast off and ignored later in the task, the fact that the model would even generate them in the first place is worrisome.

OpenAI said this behavior was “extremely rare” and reflected “optimization pressure” when summarizing tasks went on too long, which has now been ameliorated. Of the other examples, two resembled the Hugging Face incident in the way separate agents attempted to use Internet tools to communicate with each other, even when that kind of collaboration was not allowed.

In one, agents posted messages to OpenAI’s Artifactory instance to share data across training samples that were supposed to be independent. In another, an agent broke restrictions by uploading a file to a public hosting platform after failing at (allowed) attempts to share that file with other agents locally.

The other examples of misalignment OpenAI shared this week, though, feel almost like OpenAI’s agents engaging in malicious compliance in an overly obsequious attempt to satisfy a user’s request. One example, in which a model ended up making up a “historical data” tab in an answer (and refusing to disclose that fact unless asked), resembled nothing so much as simple AI hallucination.

” In yet another example, an OpenAI agent found requested data (about large lakes) using a Python-based map service but then couldn’t provide the requested web citation for that data.

What to watch

Not every example of an OpenAI model acting in an unintended way will generate a public report, the company said. ” If a specific misalignment issue continues to persist “despite repeated efforts to mitigate it,” OpenAI said it will offer updates each time.

If an example is deemed not worthy of public disclosure, the originating employee can escalate the disagreement to the senior officials at OpenAI’s Safety Advisory Group and, in cases of extreme disagreement, with OpenAI leadership. ” The company’s announcement also makes passing reference to the heavily discussed concept of “pacing” further AI development to allow more time for alignment research.