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AI Can Tell Your Political Affiliation Just by Looking at Your Face, Researchers Find (gizmodo.com)

submitted 6 months ago by return2ozma@lemmy.world to c/technology@lemmy.world

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[-] eager_eagle@lemmy.world 1 points 6 months ago* (last edited 6 months ago)

They are both mentalities

Who defines political orientation as a property of the brain? It's socially established.

[-] Buffalox@lemmy.world 3 points 6 months ago* (last edited 6 months ago)

So is crime, ultimately both stem from a sense of self interest vs right and wrong, or lack of it.

[-] eager_eagle@lemmy.world 1 points 6 months ago* (last edited 6 months ago)

idk what Phrenology or crime have anything to do with the study and I'm yet to see an argument for it

[-] Buffalox@lemmy.world 2 points 6 months ago* (last edited 6 months ago)

The headline is clearly false, you can't tell political affiliation just by looking at a persons face.
Maybe in USA you have a slightly better chance than random, because age and gender alone will give a statistical difference. But the claim of the headline remains false.

The claim of the headline is reiterated in the article:

A study recently published in the peer-reviewed American Psychologist journal claims that a combination of facial recognition and artificial intelligence technology can accurately assess a person’s political orientation by simply looking at that person’s blank, expressionless face.

Further down:

So, according to this theory, if you have a tiny face, you’re probably a progressive. Or, by contrast, if you have a big fat face, there’s a good chance you might be a Trump voter.

This simply can't be true, if it was the attempt at a Phrenology/Craniology science would have detected it 200 years ago.

[-] eager_eagle@lemmy.world 2 points 6 months ago

100% a response to the headline, which clearly must be false

It is, my bad - I thought that was obvious. The headline and the article conclusion contradict the study itself, it's just clickbait.

But the study is not invalid because of it.

this post was submitted on 24 Apr 2024

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