This was an interesting post from author of Liars and Outliers, Bruce Schneier, about the identification of sociopaths. He first quotes Scott Adams (Dilbert comic author) predicting the future identification of "sociopaths and terrorists":
My hypothesis is that science will someday be able to identify sociopaths and terrorists by their patterns of Facebook and Internet use. I'll bet normal people interact with Facebook in ways that sociopaths and terrorists couldn't duplicate.
Anyone can post fake photos and acquire lots of friends who are actually acquaintances. But I'll bet there are so many patterns and tendencies of "normal" use on Facebook that a terrorist wouldn't be able to successfully fake it.
Adams says that the reason that it would work is the same reason that fraud detection programs work: "[C]rooks don't know there is a normal pattern and so they don't know when they violate it. I think the same would be true for Facebook. There must be dozens of normal Facebook patterns that sociopaths and terrorists wouldn't know about, and therefore couldn't fake." This does not seem implausible, and is one of several reasons why I think that remaining completely anonymous and undetectable is not going to work for the rising generation of sociopaths.
Schneier has another criticism:
Okay, but so what? Imagine you had such an amazingly accurate test...then what? Do we investigate those who test positive, even though there's no suspicion that they've actually done anything? Do we follow them around? Subject them to additional screening at airports? Throw them in jail because we know the streets will be safer because of it? Do we want to live in a Minority Report world?
The problem isn't just that such a system is wrong, it's that the mathematics of testing makes this sort of thing pretty ineffective in practice. It's called the "base rate fallacy." Suppose you have a test that's 90% accurate in identifying both sociopaths and non-sociopaths. If you assume that 4% of people are sociopaths, then the chance of someone who tests positive actually being a sociopath is 26%. (For every thousand people tested, 90% of the 40 sociopaths will test positive, but so will 10% of the 960 non-sociopaths.) You have postulate a test with an amazing 99% accuracy -- only a 1% false positive rate -- even to have an 80% chance of someone testing positive actually being a sociopath.
He ends with this thought: "Many authors have written stories about thoughtcrime. Who has written about genecrime?"
The comments are also really worth reading for their intelligence and insight. For instance, there was this comment:
First you'll need a useful definition of "sociopath" that is not, for practical purposes, equivalent to "non-conformist" or "adherent to a religion not on the approved list", etc.
Followed by this comment:
You may underestimate the ability to create tautological tests. If you define a sociopath as someone who fails the sociopathy test, then the sociopathy test is 100% accurate in identifying sociopaths.
That's all well and good, until people begin to think that an attribute thus defined is useful for anything.
Showing posts with label big data. Show all posts
Showing posts with label big data. Show all posts
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