A lot of talk about AI liability focuses on courts and lawsuits. But the real question I hear in workplaces is simpler: "If something bad happens will it be my fault?” So I looked at eight cases to find out who really paid the price. The results are over the map: Individual contributors: A freelancer lost a contract with the Chicago Sun‑Times after publishing unverified AI output. An Australian lawyer faced limits on their career after submitting AI‑generated references. Managers: In one case the supervising lawyer was fined together with the employee for not checking the work. Saying “I delegated it” did not protect them. Government: Australia’s Robodebt scandal caused sanctions for servants. In the Netherlands the child‑care benefits scandal ended with the whole government resigning. Executives: After Cruise’s self‑driving incident top leaders stepped down. Everyone else: With Zillow’s home‑buying algorithm failure most rank‑and‑file employees lost their jobs while leaders stayed. The pattern: accountability is not uniform. Sometimes it hits the person to the keyboard sometimes the CEO and sometimes people who had nothing to do with the decision. One more thing I want to clear up: an AI Governance Officer is not automatically the fall guy for every failure. The job is to help the organization spot risks and set policy not to own every AI system. What stops the blame lottery is having documented ownership meaning someone who approves each system and someone who answers for it. That is a part of ISO/IEC 42001. I put the breakdown into a video if you want the case‑by‑case walkthrough, check out the latest video @ Latha-ai-governance. I have a question for everyone here: if an AI tool your team uses produced a serious error tomorrow would you know who is accountable?. Would it come down to whoever’s name was on the last email? submitted by /u/Comfortable_Gene5180
Originally posted by u/Comfortable_Gene5180 on r/ArtificialInteligence