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Comment by gzer0 | Hacker News Reader

Good points and summary. Adding on to that, the following was from the abstract about 2 sentences in. Seems like some users do enjoy jumping straight to the comments!

* Political orientation was correctly classified in 72% of liberal–conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%).

* Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples.

* Accuracy remained high (69%) even when controlling for age, gender, and ethnicity.

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"controlling for ... ethnicity"

There's significant signal buried in here that is likely not controlled for, depending on how granular their controls are.

White-German and White-Italian are much more (10-13 percent) likely to be conservative leaning than White-Irish or White-British.

Hispanic-Cuban are more likely to be conservative leaning than Hispanic-Mexican.

In the US or generally?

In the US

The words conservative and liberal have wildly other meanings outside of the US. Even in the US they are not well agreed upon (especially the definitions, people seem to know which one to pick though when they have to).

Now, what would be interesting is to build a model that accounts for this "knowledge" and see if it can beat the out-of-the-box classifier :-) I'd assume it can, and the question is: how far can a bit of manual modeling bring us?

Maybe they asked the wrong questions, but I think that's the point of the questionnaire model.

Sure, but I thought was that building an ML model that considers the questionnaire results (or existing similar findings) would be a very interesting next step.

Their section about demographics controls in the paper was really unclear (kinda surprised you can get this published being so vague).

What does a final number with the controls active even mean? I doubt accuracy was identical within each grouping they used. Even the groupings are really unclear in the paper (at most 4 ethnic groups，no idea how they did age, etc.)

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