When we say that "an algorithm is biased" we usually mean, "biased people made an algorithm." This explains why so much machine learning prediction turns into phrenology.

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Researchers with phrenological delusions ask machines to find statistical correlates of personalities or emotions, and machines dutifully provides them. It's high-stakes, machine-human collaborative apophenia, detecting patterns where none exist.

https://t.co/2b0IkQrI62

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Regrettably, this junk science gets published in respected journals. In 2017, @nature published a study by Stanford's Michal Kosinski claiming that machine learning could detect the facial correlates of homosexuality, creating an alleged AI gaydar.

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Unsurprisingly, Kosinski's study spectacularly failed to replicate. But as is so often the case, the blockbuster finding gets all the press, the careful replication work that calls it into doubt is roundly ignored.

https://t.co/J4rd6nLA4n

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Kosinski hasn't given up on AI phrenology. His lab's latest paper (published by Nature...again!) claims that he can detect political affiliation from social media photos.

https://t.co/kNPJ4vOwEr

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Spoiler: he can't.

What his system is most likely detecting is certain conventions in poses and expressions that are used in different political subcultures. Resting Karen face, basically.

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Unfortunately, this claim is being credulously reported in the tech press as true, even as the writer notes that this ML system barely outperforms random chance.

https://t.co/z1nkFFod3H

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Scientific racism has been with us for centuries. It's enjoying a renaissance today, driven in part by the neophrenologists of the ML world. They are the modern descendants of the caliper-wielding eugenicists of yore.

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To understand the genomic science that refutes all of this nonsense, you can read @AdamRutherford's brilliant, short, witty, vastly informative book HOW TO ARGUE WITH A RACIST. You'll be glad you did.

https://t.co/bPO3y5CzIX

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Image:
Cryteria (modified)
https://t.co/ICebVcdH1f

CC BY:
https://t.co/5YJhpDj3vT

eof/

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https://t.co/qnhQvROGVa


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