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Stanford staff behind BS gaydar AI says facial recognition can expose political orientation



Stanford researcher Michael Kosinski, the PhD behind the notorious “Gaydar” AI, is again with one other phrenology-adjacent (his staff swears it’s not phrenology) little bit of pseudo-scientific ridiculousness. This time, they’ve printed a paper indicating {that a} easy facial recognition algorithm can inform an individual’s political affiliation.

First issues first: The paper is known as “Facial recognition know-how can expose political orientation from naturalistic facial pictures.” You may learn it right here. Right here’s a bit from the summary:

Ubiquitous facial recognition know-how can expose people’ political orientation, as faces of liberals and conservatives constantly differ.

Second issues second: These are demonstrably false statements. Earlier than we even entertain this paper, I wish to make it fully clear that there’s completely no benefit to Kosinski and his staff’s concepts right here. Facial recognition know-how can not expose people’ political orientation.

[Related: The Stanford gaydar AI is hogwash]

For the sake of brevity I’ll sum up my objection in a easy assertion: I as soon as knew somebody who was a liberal after which they grew to become a conservative.

Whereas that’s not precisely thoughts blowing, the purpose is that political orientation is a fluid idea. No two individuals are inclined to “orient” towards a particular political ideology the identical means.

Additionally, some individuals don’t give a shit about politics, others haven’t any clue what they’re really supporting, and nonetheless others imagine they agree with one celebration however, of their ignorance, don’t understand they really help the beliefs of a special one.

Moreover: since we all know the human face doesn’t have the power to reconfigure itself just like the creature from “The Factor,” we all know that we don’t all of the sudden get liberal face if considered one of us decides to cease supporting Donald Trump and begin supporting Joe Biden.

This implies the researchers are claiming that liberals and conservatives categorical, carry, or maintain themselves in a different way. Or they’re saying you’re born a liberal or conservative and there’s nothing you are able to do about it. Each statements are virtually too silly to think about.

The examine claims that demographics (white persons are extra more likely to be conservative) and labels (given by people) had been figuring out elements in how the AI segregates individuals.

In different phrases, the staff begins with the identical undeniably false premise as many comedians: that there’s solely two sorts of individuals on this planet.

In response to the Stanford staff, the AI can decide political affiliation with larger than 70% accuracy, which is healthier than likelihood or human prediction (each being about 55% correct).

Right here’s a an analogy for a way it’s best to interpret the Stanford staff’s claims of accuracy: I can predict with 100% accuracy what number of lemons in a lemon tree are aliens from one other planet.

As a result of I’m the one one that can see the aliens within the lemons, I’m what you name a “database.” In the event you needed to coach an AI to see the aliens within the lemons, you’d want to offer your AI entry to me.

I may stand there, subsequent to your AI, and level in any respect the lemons which have aliens in them. The AI would take notes, beep out the AI equal of “mm hmm, mm hmm” and begin determining what it’s in regards to the lemons I’m pointing at that makes me assume there’s aliens in them.

Finally the AI would take a look at a brand new lemon tree and attempt to guess which lemons I would assume have lemons in them. If it had been 70% correct at guessing which lemons I assume have lemons in them, it could nonetheless be 0% correct at figuring out which lemons have aliens in them. As a result of lemons don’t have aliens in them.

That, readers, is what the Stanford staff has achieved right here and with its foolish gaydar. They’ve taught an AI to make inferences that don’t exist as a result of (that is the essential half): there’s no definable scientifically-measurable attribute for political celebration. Or queerness. One can not measure liberalness or conservativeness as a result of, like gayness, there isn’t a definable threshold.

Let’s do gayness first so you possibly can admire how silly it’s to say that an individual’s facial make-up or expression can decide such intimate particulars about an individual’s core being.

  1. In the event you’ve by no means had intercourse with a member of the identical intercourse are you homosexual? There are “straight” individuals who’ve by no means had intercourse.
  2. In the event you’re not romantically interested in members of the identical intercourse are you homosexual? There are “straight” individuals who’ve by no means been romantically interested in members of the other intercourse.
  3. In the event you was once homosexual however stopped, are you straight or homosexual?
  4. In the event you was once straight however stopped, are you straight or homosexual?
  5. Who’s the governing physique that determines should you’re straight or homosexual?
  6. When you have romantic relations and intercourse with members of the identical intercourse however you inform individuals you’re straight are you homosexual or straight?
  7. Do bisexuals, asexuals, pansexuals, demisexuals, gay-for-pay, straight-for-a-date, or simply typically confused individuals exist? Who tells them whether or not they’re homosexual or straight?

As you possibly can see, queerness isn’t a rational commodity like “vitality” or “variety of apples on that desk over there.”

The Stanford staff used “floor fact” as a measure of gayness by evaluating photos of people that stated “I’m homosexual” to photos of people that stated “I’m straight” after which fiddled with the AI‘s parameters (like tuning in an previous radio sign) till they acquired the very best attainable accuracy.

Consider it like this: I present you sheet of portraits and say “level to those that like World of Warcraft.” Whenever you’re achieved, should you didn’t guess higher than pure likelihood or the human sitting subsequent to you I say “nope, attempt once more.”

This goes on for 1000’s and 1000’s of tries till sooner or later I exclaim “eureka!” while you handle to lastly get it proper.

You haven’t discovered the best way to inform World of Warcraft gamers from their portraits, you’ve merely discovered to get that sheet proper. When the following sheet comes alongside, you’ve acquired a literal 50/50 likelihood of guessing accurately whether or not an individual in any given portrait is a WoW participant or not.

The Stanford staff can’t outline queerness or political orientation like cat-ness. You may say that’s a cat and that’s a canine as a result of we will objectively outline the character of precisely what a cat is. The one means you possibly can decide whether or not somebody is homosexual, straight, liberal, or conservative is to ask them. In any other case you’re merely observing how they look and act and deciding whether or not you imagine they’re liberal or queer or whatnot. 

The Stanford staff is asking an AI to do one thing no human can do – specifically, predict somebody’s political affiliation or sexual orientation based mostly on the best way they give the impression of being.

The underside line right here is that these foolish little methods use primary algorithms and neural community know-how from half-a-decade in the past. They’re not sensible, they’re simply perverting the literal identical know-how used to find out if one thing’s a hotdog or not.

There isn’t any optimistic use-case for this.

Worse, the authors appear to be ingesting their very own Kool Help. They admit their work is harmful, however they don’t appear to know why. Per this Tech Crunch article, Kosinski (referring to the gaydar examine) says:

We had been actually disturbed by these outcomes and spent a lot time contemplating whether or not they need to be made public in any respect. We didn’t wish to allow the very dangers that we’re warning in opposition to. The power to manage when and to whom to disclose one’s sexual orientation is essential not just for one’s well-being, but in addition for one’s security.

We felt that there’s an pressing have to make policymakers and LGBTQ communities conscious of the dangers that they’re going through. We didn’t create a privacy-invading software, however reasonably confirmed that primary and broadly used strategies pose severe privateness threats.

No, the outcomes aren’t scary as a result of they’ll out queers. They’re harmful as a result of they could possibly be misused by individuals who imagine they’ll. Predictive policing isn’t harmful as a result of it really works, it’s harmful as a result of it doesn’t work: it merely excuses historic policing patterns. And this newest piece of foolish AI improvement from the Stanford staff isn’t harmful as a result of it will possibly decide your political affiliation. It’s harmful as a result of individuals may imagine it will possibly, and there’s no good use for a system designed to breach somebody’s core ideological privateness, whether or not it really works or not.

Revealed January 14, 2021 — 20:41 UTC



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