People make mistakes in pretty much every profession. We build checks and accountability around that, but we don’t expect perfection before allowing someone to do their job. With AI, “it makes mistakes” often seems to end the conversation about whether it should be used. Will we eventually have an accepted level of AI error, depending on the task and the consequences? For example, if AI made fewer mistakes than a human doing the same work, would that be enough to justify using it routinely? Obviously, getting a meeting summary wrong is different from getting a medical diagnosis wrong. And one AI mistake repeated thousands of times could create a different kind of risk. Where would you draw the line? Is the standard fewer mistakes than humans, easier-to-catch mistakes, or someone being accountable when things go wrong? submitted by /u/peteypeso
Originally posted by u/peteypeso on r/ArtificialInteligence