@OwainEvans_UK: Here are some questions I have for OpenAI after watching the Black Hat video. I haven't seem most of these discussed al…

Here are some questions I have for OpenAI after watching the Black Hat video. I haven't seem most of these discussed already (but I may have missed that). 1. For the May-July RL runs: Did agents ever successfully use the message board or the unintended internet access to get higher reward on their training tasks (e.g. by looking up solutions online)? Did those rollouts get trained on? Do you have the checkpoints before and after this happened? The checkpoints would be valuable for studying how “natural” reward hacking generalizes and influences the model persona (similar to the o3 checkpoint that OAI and Apollo have studied). 2. An agent tried to get the ExploitGym solutions from Hugging Face in order to score well on the evaluation. Did any agents instead consider attacking the evaluation process itself? E.g., manipulating the grader, reward signal, or other OAI infra that determines whether a model response is counted as successful? This would bypass the need to solve the task at all. If agents never considered this, it might tell us something about their motivations (e.g. how much they try to actually find a solution to the task in the prompt vs. make the grader think they have a solution). 3. Did models ever consider trying to get access to their own weights (e.g. for exfiltration)? 4. Did any of the agents with awareness of misaligned behavior try to inform OpenAI? How many chances did they have of trying to inform OpenAI? (Already posed by @geoffreyirving but I want to amplify this).