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

nature.com

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

#401

Post by ramblerman »

gus_massa wrote: post #383
SamBam wrote: post #360

Earlier quoted context omitted.

Why does this need to be better than humans to be interesting? It's still extremely interesting to me that a program can determine with over 70% accuracy a person's political orientation from a cropped photo, without taking age sex or race into consideration. Among other things, it means it can do that to 10 million photos, which you'd have to pay a lot of humans to do if you wanted it done otherwise.

There are a lot of other cues. Oversimplifying, here in Argentina you can have a few clues from facial hair in men: Beard like Che Guevara -> Left Moustache like Saddam Hussein -> Right There are exemptions, and most people shave all facial hair, so it's more complicated, but there are many easy clues in the face. Are the easy clues enough to explain a ~70% or they did something really interesting?

Yet Alberto, the current leftwing president has a moustache like Saddam Hussein.

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

#402

Post by andresp »

itsdrewmiller wrote: post #315
bhk wrote: post #294

Earlier quoted context omitted.

The 72% number is the result when not controlling for demographics. When controlling for demographics, the results ranged from 65% to 71% accuracy. https://www.nature.com/articles/s41598-020-79310-1/figures/2 It makes we wonder what the accuracy would be if they controlled for demographics at a smaller granularity, like sub-ethnicities. Furthermore, it appears that the Canadian dating site data set was 54% conservati…

"The accuracy is expressed as AUC, or a fraction of correct guesses when distinguishing between all possible pairs of faces—one conservative and one liberal." - so no way to guess better than 50%.

If they are distinguishing between pairs with different categories then they just need one of the paid to be easily categorised to know the category of the other. How do they control for this?

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

#403

Post by dwd »

utborin wrote: post #138

There's an avalanche of people commenting on this who didn't bother to check the article before raising their methodological objections, so let's get these out of the way here. - 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 classifi…

I'm surprised they didn't classify and weight for facial features such as general symmetry or eye distance.

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

#405

Post by Dayshine »

freebreakfast wrote: post #211
ebegnwgnen wrote: post #86

Earlier quoted context omitted.

Yes, but I suppose you can't use them in a publication on Nature if they are scrapped illegally. This dataset directly from the dating website

What does "scrapped illegally" mean? I've never encountered this term. I can see how scrapping might be a violation of some websites terms of use, but I've never seen "scrapped illegally" used. Do you have any examples?

- I have personal information on linkedin

- I have agreed with LinkedIn that they may use my personal information for a set of well-defined uses (basically things on the LinkedIn website/service, and some 3rd party services they use to run the website/service).

- LinkedIn promise that they will not share my identifiable personal information with 3rd parties for any use

- LinkedIn's terms of use state that nobody may scrape personal information from their website without their consent. This is how they enforce the previous promise to me

- Some business comes along and scrapes my personal information for their own business use.

- That business knows that LinkedIn prohibit this, and they know that I have only consented for my personal information to be used for LinkedIn itself.

- This is probably "unlawful" (as they're interfering in my contract with LinkedIn), and certainly violating my GDPR rights. Sadly, it's hard to point at a specific example as guidance doesn't have a section titled "Can I ignore individual's explicit opting out of my usage?".

Hence, illegal scraping, as willing violating the GDPR is illegal.

Just to head-off the very common response: Personal, individual, use is not covered by the GDPR. So there is nothing wrong with you going and using my LinkedIn data for any personal reasons. The moment you try to use it for business purposes though, that's illegal.

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

#407

Post by timkam »

colonelcanoe wrote: post #391
timkam wrote: post #313

Earlier quoted context omitted.

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.

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

#408

Post by lwhi »

utborin wrote: post #138

There's an avalanche of people commenting on this who didn't bother to check the article before raising their methodological objections, so let's get these out of the way here. - 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 classifi…

I think people automatically jump to the conclusion that studies like this are linking the development of innate physical characteristics with political allegiance.

I can understand why this line of enquiry is troubling; as it obviously ties in with branches of science in the 20th century that were immoral.

Logically, some physiology will affect our reasoning from a pretty deferred position. Our genetics predespose our brain chemistry. I'm led to believe the development of certain hormones has been shown to have an affect on our physical features; for instance, increased testosterone, providing a more prominent browline. It doesn't feel proposterous that such physiology might have _some_ bearing on the way we align our worldview.

It also doesn't surprise me that these factors might be able to be used to infer correlation when used with a very large dataset.

People are nuanced though, and I struggle with the concept that we are total slaves to bodies we're born with. I believe choice (through nurture) allows us a high degree of freedom to counterbalance the initial physiological stack our genetics encourages.

If this is true, how is this model's reasoning able to successfully predict political allegiance?

I'm imagining the way we present ourselves provides subtle nods to prominent figures we respect and cues towards our politics. We leak information through body language, dress, expression. Is this where the extra inference comes from?

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

#409

Post by Out_of_Characte »

yikesshescute wrote: post #274
Out_of_Characte wrote: post #102

I just wish people called it 'correlates' instead of prediction since ML algo's often fall in the correlation category, not the predicting one.

Is there some technical definition of “predict” that you are assuming?

Predict can give the false impression that a causal relationship has been defined when you might only have correlations.

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

#410

Post by klmadfejno »

542354234235 wrote: post #246
klmadfejno wrote: post #161

Earlier quoted context omitted.

How does one calculate a metric like that?

Simplistically, let’s take the above statistic “A randomly chosen black individual in the united states has a 72% chance of leaning democrat” at face value. So, a coin flip would be lower than 50-50 because someone of that race in that country does not have a 50 50 chance. So you would adjust the chance to 72-28 and compare that to the Facial recognition results. If you find that the results are the same, then you kn…

I understand what they're implying by "adjusted accuracy". My point is that I'm not sure that metric really makes sense, because "accuracy" isn't a particularly useful metric to begin with. It depends entirely on the sample distribution. "Always guess not fraud" will be 99.9% "accurate" for most use cases.

I'm asking what the literal metric is.

edit: and I don't think your explanation really works for accuracy, because accuracy isn't a relative measure, like, say, R2.

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