posted on September 25, 2020 07:20 PM by
u/brokenAmmonite
34
u/DELETED24 pointsat 1601093506.000000
As a (non-tenured) professor working at the intersection of machine
learning and causal inference, I cannot begin to express how depressing
it is that this ended up in fucking Nature. Why do I bother to
try to do careful work?
All you really need apparently is a few Pinker citations and some
dipshit undergrad to run a fucking facial recognition Python
library.
> working at the intersection of machine learning and causal inference
Ooh, ooh, ooh, super cool. What is that you do specifically? I feel like there isnt nearly enough development in this area.
Though there's a ton of work in this area. Everyone is trying to figure out a way to mix ML "discovery" with CI "identification" (at least that's my sense from my corner).
Perhaps I’m misreading something or being too generous, but it
doesn’t seem to me that the author is saying anything about
actual trustworthiness, but rather only perceived
trustworthiness, including all of our biases. In this
tweet he says they compared their model to make sure it had all the
biases that humans have when we unconsciously judge trustworthiness. Or
at least some of the biases - he manages not to mention race.
No, they trace how our _current, interconnected_ "perception" of "trutworthiness" maps to a historical selection of portraits.
And they routinely conflate it with _actual_ trustworthiness.
the lead author's bio:
> Evolutionary Psychology for the Social Sciences. Morality, Religion, Public Policy, History, Economic Development.
0% chance he hasn't read moldbug
He’s French and is an university academic and very high up in a French Government Scientific Institute per his website bio. He seems fine, this may not have the same resonance as an issue in France
As a (non-tenured) professor working at the intersection of machine learning and causal inference, I cannot begin to express how depressing it is that this ended up in fucking Nature. Why do I bother to try to do careful work?
All you really need apparently is a few Pinker citations and some dipshit undergrad to run a fucking facial recognition Python library.
Perhaps I’m misreading something or being too generous, but it doesn’t seem to me that the author is saying anything about actual trustworthiness, but rather only perceived trustworthiness, including all of our biases. In this tweet he says they compared their model to make sure it had all the biases that humans have when we unconsciously judge trustworthiness. Or at least some of the biases - he manages not to mention race.
Am I missing something?
Excuse me, sir, this is physiognomy, not phrenology.
scooped by 118 years
Sorry but just no, phrenology isn’t the same thing as “We tend to judge people based on their physical appearance”.
Isn’t it great how blatantly they are associating skull shape with trustworthiness?
Whew lad.
Skull calipers seem to be coming back into fashion like so many other things from the 20s.