"Systematic, correctable mistake" is not the way to describe errors made by AI algorithms, and definitely not in the context of an engineered system containing

"Systematic, correctable mistake" is not the way to describe errors made by AI algorithms, and definitely not in the context of an engineered system containing many algorithms and sensors. In general, AI algorithms are famously opaque and hard to debug. It's too long to explain here, but here are some links: https://en.wikipedia.org/wiki/Explainable_artificial_intelligence https://en.wikipedia.org/wiki/Explainable_artificial_intelli... https://www.wired.com/story/greedy-brittle-opaque-and-shallow-the-downsides-to-deep-learning/?verso=true https://www.wired.com/story/greedy-brittle-opaque-and-shallo... https://blogs.wsj.com/cio/2018/05/02/companies-grapple-with-ais-opaque-decision-making-process/ https://blogs.wsj.com/cio/2018/05/02/companies-grapple-with-... https://thenextweb.com/artificial-intelligence/2017/04/23/artificial-intelligence-has-to-deal-with-its-transparency-problems/ https://thenextweb.com/artificial-intelligence/2017/04/23/ar... https://towardsdatascience.com/need-for-explainability-in-ai-and-robotics-75dc6077c9fa https://towardsdatascience.com/need-for-explainability-in-ai... https://www.forbes.com/sites/cognitiveworld/2018/12/20/geoff-hinton-dismissed-the-need-for-explainable-ai-8-experts-explain-why-hes-wrong/#46c5b009756d https://www.forbes.com/sites/cognitiveworld/2018/12/20/geoff... ----- BTW I'm also a cyclist. Human drivers can be annoying, but I find that they do act predictably. I've been cycling 5+ days a week in SF for 10+ years. I find that the drivers are worse when I bike in cities where bikes aren't as prevalent. Humans do learn. When you get into a conflict, there are emotions, and emotions are mechanisms for learning :) It seems like you think that an AI is "just" a computer program, where the errors ARE indeed systematic and correctable. But AI is fundamentally different.