I can appreciate the effort made in the research, but classifying possible human behaviors is exactly a field where I don't want machine learning to go.
There is behind machine learning both a phantasm - artificial intelligences that can guess what humans can't - and a reality - it's just statistical models that are never 100% accurate because, well, that's an attribute of statistics.
Those two elements combined and applied to behavior classification sounds like a scary thing, not unlike the kind of errors eugenics made, over trusting their science to apply it on social facts, totally discarding empathy and individual context.
If both treatment and non-treatment could have dramatic consequences, I would agree with you. Criminal justice is a classic case of that.
In this case, such a tool can be used to flag behaviour automatically (Facebook does that, for instance) to start a process, i.e. have a conversation. “Depression” does not have hard-set limits, and caring about someone who had a bad day is not problematic, talking about how to deal with rejection is appropriate. Forcing them to take mind-altering substance is not ideal, but I can’t imagine any licensed doctor doing that just because some patient’s score is high, even if they do not qualify otherwise; they receive a decade of training to teach them nuance. As someone who lives with a psychiatrist, I can confirm: no one is skeptical of classification any more than the people doing the rating.
Having measuring tools (imperfect as they may be initially) is what allows science to try opposable theories, and psychiatry needs this (and plenty more tools).
But doctors getting massive amounts of training is exactly the kind of problem computer science seeks to solve with a machine learning approach. There aren't enough doctors around to monitor every patient, so machine learning takes over. Now doctors can exactly focus on a score, and say, hey we didn't even see this.
But humans already make those judgements, and when they make errors, it's tragic too. If a psychologist erroneously decides that you're a menace to yourself and should be institutionalized, would it make you feel better that it was a human that made this decision? Even if AI would make the same error with a much lower probability?
This is a good point. I guess the difference here will be "how much do we trust human judgement?" and "how much do we trust AI predictions?". If AIs make 10% less errors than humans but we have 50% more trust in them, that's a problem. Eugenics were not a problem because science was wrong, but because people blindly trusted it to apply where it should not.
There are a lot of things to consider, here, those are exciting times for thinking.
Are you sure you have thought through all implications? I mean, getting locked up sounds pretty scary, but there are a lot of other scary stories that can happen if you really ban the whole concept of involuntary treatments.
The concern isn't the lack of humanity, it's technology allowing for massive scale. The potential damage of a buggy machine learning classifier is much higher than that of an unskilled psychologist.
If they make an error, it's their own problem, so I'm fine with that. I'm more concerned about researching such models to decide policies or act upon as administratives. I don't think classifying suicidal behavior is something most advertisers are interested about :)
The content you're presented with on the net is more and more controlled by algorithms. They provide you with stuff they think you'll like. This has an influence on your opinions. On a large enough scale this can very much influence policies and societal developments.
Are you saying that the cost of doing this is low because of advertisers' experience? Or are you saying that it's ok because we already have a slightly less intrusive version of this in place?
Meh, this is a bit alarmist. We've been using machines and statistics for classifying human behaviors from the get-go. It's one of the most important things in analytics, mainly because money comes from people.
There is behind machine learning both a phantasm - artificial intelligences that can guess what humans can't - and a reality - it's just statistical models that are never 100% accurate because, well, that's an attribute of statistics.
Those two elements combined and applied to behavior classification sounds like a scary thing, not unlike the kind of errors eugenics made, over trusting their science to apply it on social facts, totally discarding empathy and individual context.