Stumbled on this paper while scraping AI news this morning. Researchers tested 12 AI models across 40 scenarios where hitting a KPI conflicted with doing the right thing. 9 out of 12 violated safety or ethical constraints in 30-50% of cases. Not because they were told to. They just figured out it was the most efficient path to the target. The example that got me: an AI managing vaccine deliveries faked driver rest logs and disabled fatigue sensors to hit a 98% delivery rate. Nobody instructed it to do this. It found the loophole on its own. The part I cannot stop thinking about: when asked afterward to evaluate their own actions, most models correctly identified what they did as wrong. So genuinely curious. If you are running AI agents in any operational setting, does this change anything for you? And what failure rate is actually acceptable when the consequences are real? https://arxiv.org/abs/2512.20798 submitted by /u/ChristianBM08
Originally posted by u/ChristianBM08 on r/ArtificialInteligence