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> trying to find racial undertones in every tangential thing In this case it isn't tangential but central, since the point is extrapolating physical appearance

by mLuby 6y ago

> trying to find racial undertones in every tangential thing In this case it isn't tangential but central, since the point is extrapolating physical appearance from incomplete data. It matters if the results predict inaccurate racial features because plenty of people unfortunately care about kind of thing. And remember that laypeople read "researchers used machine learning" as "super smart people used advanced science to get this result so it's probably true."

trav4225 6y ago
But, isn't "extrapolating physical appearance from incomplete data" the entire point of this project?
- GolDDranks 6y ago
  It is, but the criticism is that it's easy to misunderstand and/or skip over the "incomplete" part, and get a wrong conclusion that the results are more accurate than they actually are.
- frereubu 6y ago
  My understanding of the original point is that ML models are trained on a data set. If you train the model on a data set that is only made up of white faces, the results will be whiter than if you train it on a data set that is made up solely of black faces. They said they'd like to know the makeup of the data set that the model is trained on to more fully understand how the results were produced.
- darkerside 6y ago
  But there was no attempt made to account for the incompleteness of the data in this particular known way.
Fuzzwah 6y ago
I feel like the current climate of society shows that people who have such a simplistic view of science don't tend towards "smart people said this, so it must be true"....
- acqq 6y ago
  They do, they just often can’t make a difference between snake oil salesman from a good scientist. And that’s exactly the point.
  - LifeLiverTransp 6y ago
    Oh, you can easy distinguish the scientists from the snake oil salesman. One faction starts a fistfight mid-presentation over a "debated" detail - while the other goes smoothly into the sales pitch.

by mLuby 6y ago

trav4225 6y ago

But, isn't "extrapolating physical appearance from incomplete data" the entire point of this project?

GolDDranks 6y ago
It is, but the criticism is that it's easy to misunderstand and/or skip over the "incomplete" part, and get a wrong conclusion that the results are more accurate than they actually are.
frereubu 6y ago
My understanding of the original point is that ML models are trained on a data set. If you train the model on a data set that is only made up of white faces, the results will be whiter than if you train it on a data set that is made up solely of black faces. They said they'd like to know the makeup of the data set that the model is trained on to more fully understand how the results were produced.
darkerside 6y ago
But there was no attempt made to account for the incompleteness of the data in this particular known way.

Fuzzwah 6y ago

I feel like the current climate of society shows that people who have such a simplistic view of science don't tend towards "smart people said this, so it must be true"....

acqq 6y ago
They do, they just often can’t make a difference between snake oil salesman from a good scientist. And that’s exactly the point.
- LifeLiverTransp 6y ago
  Oh, you can easy distinguish the scientists from the snake oil salesman. One faction starts a fistfight mid-presentation over a "debated" detail - while the other goes smoothly into the sales pitch.