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The Economist on using phrenology for hiring and lending decisions: "Some might argue that face-based analysis is more meritocratic" […] "For people without access to credit, that could be a blessing" (lemmy.ml)
submitted 1 year ago by to c/technology@lemmy.world
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cross-posted from: https://lemmy.ml/post/38830374

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economist article

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https://en.wikipedia.org/wiki/Phrenology

excerpts of economist article:

screenshot of text "Imagine appearing for a job interview and, without saying a single word, being told that you are not getting the role because your face didn’t fit. You would assume discrimination, and might even contemplate litigation. But what if bias was not the reason? What if your face gave genuinely useful clues about your probable performance at work? That question is at the heart of a recent research"

[...]

screenshot of text "a shorter one. Some might argue that face-based analysis is more meritocratic than processes which reward, say, educational attainment. Kelly Shue of the Yale School of Management, one of the new paper’s authors, says they are now looking at whether AI facial analysis can give lenders useful clues about a person’s propensity to repay loans. For people without access to credit, that could be a blessing."

screenshot of a tweet from @TheEconomist on Nov 8 2025 with text "What if your face gave genuinely useful clues about your probable performance at work? That question is at the heart of a recent paper"
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[–] 1 point 1 year ago

A classification problem is correlation vs causation. Sunspots and mini skirts have been correlated with stock market returns to some degree, but it tends to be a tenuous connection not guaranteed to hold up over time, or to actually have any meaningful relevance whatsoever. It's easy to oversell models.

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