Facial recognition can predict person’s political orientation with 72% accuracy

- Yes, they controlled for objects appearing in the pictures that might indicate political affiliation. The images are tightly cropped around the face. See Methods.

- Yes, this is significantly better than both a coin flip and a human classifier. They gave the same test to humans, who did much worse than the model. See Abstract, Introduction, and Results.

- Yes, this is doing more than just detecting a person's race, age, and/or gender. The classifier is still accurate when they compare people with the same race, age, and gender. See Results.

If you want to discuss actual limitations in the study, here are some the author points out:

- "A more detailed picture could be obtained by exploring the links between political orientation and facial features extracted from images taken in a standardized setting while controlling for facial hair, grooming, facial expression, and head orientation."

- "Another factor affecting classification accuracy is the quality of the political orientation estimates. While the dichotomous representation used here (i.e., conservative vs. liberal) is widely used in the literature, it offers only a crude estimate of the complex interpersonal differences in ideology. Moreover, self-reported political labels suffer from the reference group effect: respondents’ tendency to assess their traits in the context of the salient comparison group."

It's a study which shows that pictures that people select to represent themselves publicly have features that indicate political leaning.

> 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%).

This isn't a matter of "recognize that old white people are conservative", because people will do that already, and they know all those biases. And the system doesn't lose much accuracy when comparing otherwise similar people.

This system is picking up on things we don't notice. Maybe it's the photos themselves (they are self-selected), maybe it's micro expressions in the face, maybe it's something else entirely.

But damn it's neat and maybe frightening. Imagine if your next hiring manager had a quiet little camera in the corner and chose you based on your predicted approval of unions.

It doesn't sound like people were consenting/aware that they'll endup on a facial recognition study.

But I'm not even surprised dating website would sell their such data

So, this seems to be doing profile picture recognition, not facial recognition. It's not like they're saying there are physical features in your face that give away your political affiliation - that is to say, putting two people's bodies under the same photographic conditions would probably not create this kind of signal.

What this is probably training on is the cues for cultural values that we self-select in our most deliberately promoted images of ourselves. If you have a carefully-chosen profile picture, it probably includes signals of what's important to you, especially if you're using it to attract people with similar values.

I eventually started a game in my mind where I'd try to guess their political affiliation before the chyron appeared. I'm pretty sure by the end I was getting it correct more than 50% of the time. Everyone was dressed similarly, but I remember looking closely at their tie patterns and hair cuts as clues.

Grey tribe members may beg to differ

https://www.gsb.stanford.edu/insights/rise-liberaltarian

Edit: One last rant about this palm-reading-esque pseudoscience: I hate that this was put out in the universe, and thus potentially giving the wrong person ideas.

I think there's huge value now that everything is being sent into a "machine" or "the algorithm" in fucking with it.

Order sex toys from Amazon, show them you're into outrageous books and fool them into creating a fake profile of "you", based on your spending, browsing and other data you generate.

I'd love to ask a machine what it knows about me, how accurate it is, and then switch it all up. I'm too old to vote now (and will probably be dead soon) but I'd love to pick a position completely unexpected just to throw it off.

Poison the well

Accuracy issues are a feature not a bug! Now you've sown a bunch of discontent and suspicion within their communities.

It’d be interesting to do the same analysis with photos of people taken 10, 20, 30, 40,... 100 years ago to see if the intersection (28%) grows/shrinks historically. Were we always so easily politically separable by our appearance alone?

Has our appearance always revealed our political leanings, or do we now dress in order to make a political statement?

That should give you a lot more hints than a still image.

The worst possible uses: filtering out undesirable people applying for jobs or for college, firing people who are suspect of belonging to a different political tribe.

It's not that it's always trivial to figure out what's happening inside a model like this, but I'm surprised that no attempt seems to have been made: modifying images and seeing which increases the scores, bringing in a co-author who actually understands what the model is doing, seeing if they can obtain similar results with a more interpretable model. Am I wrong, and in fact fining out what's actually happening is impossible, or of no benefit?

I was going to ask how they controlled for the presence of compound bows & deer, trucks, and tank tops in the photos, but this implies they did not. Another one would be lighting palette, since that's going to be biased to regions as well. There is something to be said for it, as I'd say I have a %72 chance of guessing someones political orientation by looking at them as well, which someone once explained to me as being the effect of testosterone levels on the region around their eyes, but that sounded like folksy bro science.

Employers, condos, schools, many communities will want to ML-screen candidates, be it officially or not..

- The rest of the word.

In the US, African Americans vote overwhelmingly for democrats for example. Skin color therefore becomes a very good predictor of political orientation. You can probably extend this to states being populated from various migration waves, say 'people who look like Danes vote for republicans because state X was populated by Danes and votes Republican' . Carry this across generations/education, and you may have an explanation.

Representing the conservative and liberal groups as gaussian mixes of multiple atributes, I would expect those two peaks to overlap. Perhaps the real surprise is that they overlap no more than 28%.

Also, whoever makes the first app for this will go viral 100%.

In general, though, its amazing how little control we have over who we are despite the feeling that we are in control of it.

So if I just assign the majority label to all of the population of a given demographics group, I would get the same result right? i.e., predicting "left" for all minorities under 30. You would also get ~70% accuracy.

An interesting question, to me, is: how would you (personally) react if such an controversial and stigmatized factoid would be proven true at more than 5 sigma?

Would you be shocked? Or would you accept the outcome? And which of both would tell what of yourself?

Throw an ML engineer at this task and you could probably do * way * better than 72%.

Would't this legitimate all these voices who ever said I can tell you by just looking?

This skims somewhat close to people who tried to infer criminality from facial and cranial characteristics... a century ago

I think the incomes of people on the right skew lower, or they have fashions for makeup, facial hair etc. I'd be interested in an adversarial attack on the classifier.

That is an extremely loose assumption.

Not sure I’m entirely comfortable with that.

This sounds more like people who are from minority groups (or who look like they are, to a computer vision algorithm) are more likely to agree with left-leaning policies, which probably has more to do with the policies in those countries than it does with any sort of genetic features. I feel like this might not work as well in non-Western countries, for example.

We all know there is a demographics/ethnics factor in people's political affiliation.

> Both in real life and in our sample, the classification of political orientation is to some extent enabled by demographic traits clearly displayed on participants’ faces. For example, as evidenced in literature and Table 1, in the U.S., white people, older people, and males are more likely to be conservatives.

Most people can predict a person's political orientation of their own country with >50% accuracy as well just by looking at a face. Black or latino? probably liberal. Old white person? probably conservative. If you can see more than just their face it's even easier (wearing religious paraphernalia? LGBT paraphernalia? etc?)

What I thought was interesting was:

> The algorithm could successfully predict political orientation across countries

I was under the impression that "liberal" and "conservative" had different meanings in UK vs. USA so how could it do this?

This is really interesting. I never considered head orientation or expression to be a factor. Then again, it sorta makes sense. Speaking very generally, liberal leaning people on social media probably tend to be more likely to post pictures of themselves in a humorous or "soy face" expression, and conservative-leaning types may try to look strong or aggressive.

Also, I automatically assumed features like "handlebar moustache" would mean more likely to be conservative, but it sounds like facial hair wasn't as big a factor.

Not only that, it is hackable, and somewhat mutable… and I think that can reflect back into one's general attitude on life. I'm going to share some personal notes on my own face hacking done to serve my purposes as a youtuber and open source coder…

The key phrase here is, "The highest predictive power was afforded by head orientation (58%), followed by emotional expression (57%). Liberals tended to face the camera more directly, were more likely to express surprise, and less likely to express disgust." People will respond to you based on what your face is doing, and be more or less favorably disposed to you if you 'match' where they're at.

Guy Kawasaki's on record as trying to maximize his ability to Duchenne smile (crinkle the outside edges of the eyes as your cheeks go up) in order to better influence others. You can make special efforts to dry your skin there, the better to form heavy wrinkles that can come into play, signalling affability and well-disposedness as a proper Duchenne smile would do.

But there's another area. If you fret a lot, or glower, your brow comes down and wrinkles form where your brow meets your nose. This signals suspicion, disgust, hostility. My face-hacking involves putting Nivea cream there and on my forehead, keeping that skin more flexible and mobile, for a more open affable look. But if you're targeting a conservative audience you can do the opposite: look at Tucker Carlson sometime. You can cultivate a world-weary scowl and it will increase your trust with people sharing a similar facial expression, and tend to concentrate your viewer's expressions into ones similar to your own (while you tell them scowl-worthy things), so long as you have their basic trust to start with.

This is all very malleable. Very hackable. You can do it on purpose. I don't know if Tucker Carlson does scowl exercises, but I know if he botoxed his brow scrunch, he would be less effective as a political commentator, because he would be telegraphing the intended reaction to his information more weakly.

We're looking at a general connection between human resting facial expression, and human overall outlook on life. I didn't expect to run across this study but I find it absolutely plausible. Almost axiomatic. You can even frame it in ways that appear to favor one political side or the other, but the underlying principle tells us a lot about how political orientations arise.

When I lived in Texas, I was considered a liberal. When I moved to Chicago, I was considered a conservative. When I moved to Seattle, I was considered a conservative. When I moved to the desert southwest, I was considered a liberal. Nothing about my face changed. Just my address.

I swear to fuck. All this praise to repeat the sins of the 20th century all over again? But oh no, it's okay because it's done by "software engineers".

That and you "atheists techies" are just as fanatically religious as jihadists. Instead of a deity, you worship silicon valley and algorithms.

Of course tech companies can be trusted with our data.

Theres nothing to fear from putting your life on social media if you have nothing to hide.

A select few should have absolute say on what we are allowed to even consider "free speech".

Tech companies aren't in it for profit, they're in it to save the world because they're the "educated elite".

Just... why is this not being shot down? Are you that blind to where it's going to lead? Its literally the same steps every other totialirian psychopath took. Mass identification on bullshit pseudoscience. Then comes the extermination.