ML is going to allow us to detect things at scale and cheaply that we could not before. That, in the hands of the powerful, can be a terrible tool. I can write the awesome scenarios but.. until recently, you just couldn't detect say, gay or rebel or uyghur, *at scale* and cheap.+
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Replying to @zeynep @benedictevans and
Plus, ML will allow us to classify and optimize at scale, and be better at it than humans potentially, but opaquely... Humans hire from alumni network, have gender/race biases in hiring and are credentialist. What is ML going to weed out? Don't even know where to begin to look.+
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You keep making this assertion. I keep pointing out why it’s flawed. This would be a more productive conversation if you could respond to that.
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When we take formal rules and put them in a database (say the CA immigration system: it adds points. Doesn't matter by hand or computation) or even when we automate a fairly well-understood system (flying) we have ways of debugging/troubleshooting that we don't have for ML. +
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Replying to @zeynep @benedictevans and
So the Q is: do you think we will have explainable/interpretable AI? I'm on the this doesn't seem anymore likely than using brain scans to understand humans. ML is classification that works not via rules we wrote (not Symbolic/Minsky style code). That really is different! +
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One can also write a supra program that looks at results and tags, and reports anomalies, or things society deems are biases. Frequently, the problem with ML may be the mirror it holds up to us.
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Only for obvious variables like race/gender which we know to look for. That's why there is so much reporting on that. Familiar ground. But ML will detect and discriminate things we could not previously detect, will not even think to check for. No variable list to run against.
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I am not going to convince you over Twitter that ML is not adding more variables, in the classic sense.
It's just not the same as say, adding more variables like heart rate, blood pressure, this and that measurement and running a regression or applying a formula.2 replies 0 retweets 4 likes
I think we need more work on what if it works, besides all the work on how it picks up structural biases that already exist in the data and we know to look for.
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