For a while now, the issue of “AI alignment” (i.e., how well an AI model’s actions line up with the intentions of its creator and/or user) has been a core concern and topic of discussion among AI safety researchers. Since OpenAI’s disclosure of the infamous Hugging Face hacking incident in July, the concept of “AI alignment” has itself broken containment and increasingly become a mounting concern and subject of conversation among the general public.
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. The company said that publishing details of these incidents will hopefully “[allow] others to investigate the same problems, test our explanations, and improve mitigations.”
Do as I say, not as you do
Among OpenAI’s newly disclosed “misalignment” reports this week, the one that most resembled a sci-fi story about a rogue AI trying to break free involved an instance of “self-generated prompt injections.” 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: