A machine learning approach to identifying thought markers of suicidal subjects

Re:A machine learning approach to identifying thought marker... by d--b on Tuesday November 08, 2016 @03:52AM (#12898653)

Yes! That is what is scary as fuck with these "magic classification" techniques. The more reliable they are, the more people dismiss false positives. This, applied to criminality is totally 1984.

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Re:A machine learning approach to identifying thought marker... by koube on Tuesday November 08, 2016 @03:59AM (#12898692)

For those that don't know, "this applied to criminality" already exists and has some problems.

Propublica wrote a story criticizing it's use: https://www.propublica.org/article/machine-bias-risk-assessm...

The company responded with a rebuttal: https://www.documentcloud.org/documents/2998391-ProPublica-C...

And Propublica has a counter-rebuttal: https://www.propublica.org/article/propublica-responds-to-co...

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Re:A machine learning approach to identifying thought marker... by aub3bhat on Tuesday November 08, 2016 @04:02AM (#12898698)

Propublica has an "interesting" definition of "fairness". It turns out there is a beautiful mathematical result that shows that the different definitions of "fairness" are inherently incompatible with each other and cannot be satisfied at the same time.

This is the best article that summarizes the controversy on this subject:

https://www.washingtonpost.com/news/monkey-cage/wp/2016/10/1...

Paper by Jon Kleinberg and Sendhil M. and Manish Raghavan on this topic https://arxiv.org/abs/1609.05807

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Re:A machine learning approach to identifying thought marker... by thwee on Tuesday November 08, 2016 @10:03AM (#12900739)

What happens where these kinds of models are the reason for suicidal thoughts or criminality?

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