There is an entire industry geared towards influencing mass media, and newspapers have had a lot of pressure on them—from subscribers to protests to regulation in many countries to journalism schools to codes of ethics to flak.. Media is both analyzable and often pressured.
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I think the current convo on AI/ML is what if it is wrong in the sense it reflects the biases in the training data which are often structural biases in human societies. I'm asking something different: what if it works, and detects something we previously could not—not at scale.
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And it's opacity means that we don't even know whatever latent thing it's using to classify. Instead of not hiring based on race, it's not hiring based on propensity to depression—and nobody knows that's what it's doing. No variable labeled "prop_depression". Just a giant matrix.
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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. - Show replies
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