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Huh? In my experience, people who make a mistake tend to make the same mistake again and again. Whereas, when a machine makes that mistake, somebody fixes the b

Huh? In my experience, people who make a mistake tend to make the same mistake again and again. Whereas, when a machine makes that mistake, somebody fixes the bug and it doesn't happen again. If the machine can teach itself, then so much the better, but "has someone supporting it" is a sufficient form of "learning from itself in production" to address the concern you raise. In the industry where I've been working for the last past several years (finance), when something goes wrong, the first instinct everyone has is to bump up the prioritization of automating whatever human task was responsible for the human error. And the automation is pretty much only bounded by the amount that the company is willing to spend on programmers and its ability to find good programmers who are willing to work for it and its insistence on maintaining backwards compatibility with bad legacy systems.

lqet 6y ago
> Whereas, when a machine makes that mistake, somebody fixes the bug and it doesn't happen again. Well, that is kind of the problem with AI. How do you fix a "bug" (if you can even call it that) in a model you cannot fully understand? Do you re-train it on the catastrophic mistake and somehow give it more weight? How can you be sure that this won't lead to any problems where previously there were none? How do you explain to a customer that your model now doesn't make mistake A anymore, but now mistakes B and C frequently occur? The only safe bet is to write some auxiliary code, which first uses the AI as a black box, and afterwards explicitly checks the result for this particular mistake. If this happens again, and again, and again, you need a human to maintain and extend this auxiliary code and also adjust it to changes in the underlying model, at which point I am quite certain just using a person of average intelligence instead of AI will be cheaper, more reliable and more flexible.

lqet 6y ago

> Whereas, when a machine makes that mistake, somebody fixes the bug and it doesn't happen again. Well, that is kind of the problem with AI. How do you fix a "bug" (if you can even call it that) in a model you cannot fully understand? Do you re-train it on the catastrophic mistake and somehow give it more weight? How can you be sure that this won't lead to any problems where previously there were none? How do you explain to a customer that your model now doesn't make mistake A anymore, but now mistakes B and C frequently occur? The only safe bet is to write some auxiliary code, which first uses the AI as a black box, and afterwards explicitly checks the result for this particular mistake. If this happens again, and again, and again, you need a human to maintain and extend this auxiliary code and also adjust it to changes in the underlying model, at which point I am quite certain just using a person of average intelligence instead of AI will be cheaper, more reliable and more flexible.