
Artificial Intelligence and the Resurgence of Physiognomy - anarbadalov
https://undark.org/article/facing-facts-artificial-intelligence/
======
nerdponx
_In his paper, Kosinski said the computer was zeroing in on certain physical
features of the face consistent with prenatal hormone theory (PHT), which
suggests that gay people are so because they were exposed to differing levels
of androgens in the womb. “The faces of gay men and lesbians had gender-
atypical features,” the scientist wrote, “as predicted by the PHT.” Kosinski
argues that prenatal hormone theory is “widely accepted” as a model for the
origin of homosexuality._

Did they control for the actual contents of the photos? For the position and
expression on the faces? Nope!

 _Yet even Kosinski admitted that the computer might be picking up something
besides immutable facial features. His algorithm, for example, posits that gay
men are more likely to wear glasses. “Many wondered why faces with glasses are
considered by algorithm to be more likely to be gay,” Kosinski said. “It might
be something else in the face that’s also correlated with having glasses.”_

This sounds like a classic case of the "Neural Net Tank Urban Legend", which
was discussed here recently [0].

[0]:
[https://news.ycombinator.com/item?id=15485538](https://news.ycombinator.com/item?id=15485538)

\--------------

 _Jonathan Frankle, a Ph.D. student at MIT who served as the staff
technologist at Georgetown University’s Center on Privacy and Technology, said
we often don’t know how these sorts of algorithms work. Unlike ordinary code,
a neural net involves nodes that are interconnected, with processes happening
in parallel. A neural net isn’t just executing a set of instructions in
sequence; instead the nodes are talking to each other, giving feedback to each
other. There really isn’t any way to trace how it makes its decisions — one
can’t look at a single line of code or subroutine. It’s effectively a black
box._

I hate this. It's wrong. You absolutely can trace the execution of a neural
network in its decision making. It might be hard to understand, but there's
nothing stopping you from looking at node activation patterns.

There is also a whole class of techniques for extracting some kind of meaning
out of these black-box-type classifiers. See LIME [1] and older technique
called "partial dependence" [2].

[1]: [https://github.com/marcotcr/lime](https://github.com/marcotcr/lime)

[2]: [https://github.com/bgreenwell/pdp](https://github.com/bgreenwell/pdp)

~~~
heavenlyblue
Or, you know - gay people just tend to wear glasses because it's fashionable.
Network effects and everything.

PS: before I get slammed for over-generalising - that is more of an meta-
ironic statement

~~~
Chris2048
Have a meta-ironic upvote (downvote).

------
ShabbosGoy
Reminds me of the anime "Psycho Pass". It's set in the not-so-distant future
where everyone is monitored and assigned a "crime coefficient". Without giving
too much away, the system starts to show its weaknesses when a criminal is
able to murder people and commit crimes without being detected by the system.

------
bayesian_horse
The shape of an eyebrow does not indicate an extrovert, at least not with any
better accuracy, than a Human interviewer can achieve with five minutes of
conversation. And then there is the question whether introvertedness is even a
disqualifying trait in a sales representative. A good team will probably have
both introverts and extroverts at some ratio.

Yes, it's "bad science". But it's also bad business. It's the same with
genetics: As soon as we have a full understanding of risk factors and
beneficial traits, and we're far from that, people competing for a job would
probably all have multiple "bad" and multiple "good" qualities, which cancel
out much of the benefits of testing in the first place.

