Thats what I said, better than humans is not good enough. Humans can make mistakes but they can be held accountable and their mistake is not an accepted outcome

Thats what I said, better than humans is not good enough. Humans can make mistakes but they can be held accountable and their mistake is not an accepted outcome of the system. To put it differently, facial recongition would be compared with explicitly accepting only low IQ people for cop jobs (which some PDs do!) as opposed to hiring the best people and expecting them to have 100% accuracy. Their mistake is a matter of judgement and negligence. Facial recongition's mistakes are a matter of the system accepting the mistake. Technical people often focus on the pure metrics but as in engineering,why faults happen is important. The metric should never be the goal. To put it differently, explicitly accepting injustice is incompatible with mine and I believe society's understanding of justice. This is the same reason why ML shouldn't be used to replace human judges regardless of improvements in outcome. The authority of judges,cops and legislators is legitimate because the people have a contract with them where the people's view of justice is implemented as law in return the people subject themselves to these laws. Facial recogntion and ML judges violate that contract and as a result the outcome is illegitimate,100% of convicts become wrongly convicted because as a people the views on justice of their society was nor enforced by a member of their society that is elected or appointed by the people but by a blackbox logic that only looks at the outcome as a metric. A defense attorney can claim eyewitness testimony is inaccurate for example and cross examine witnesses but that attorney cannot interrogate a ML presenting as evidence a blurry picture with a 99% accuracy match.