Great points. a) a case of misalignment - the AI’s goal was to pass the test, but was never instructed to stay within parameters, so when it found a possible method for improving its odds, the goal pushed it to try them. The misalignment is not the goal or the test, but the understanding of restrictions. Human error or incompetence. b) that persistence is why it can often do things that look smart, because it’s tried all sorts of angles and looked through training in milliseconds. And going back to a), it will try everything to make sure it gets the best goal results, so any overlook means lots of processing time to do something that might not have been the intent of the prompt.