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Comment by coldtea | Hacker News Reader

>It doesn't, because there is no explanation for how it determines the difference.

You don't need to know the mechanism to prove that it "supports the theory that there is a difference in brain organization". If there wasn't a difference, it wouldn't be able to find it.

>It's just as likely some confounding thing that's not causally based on the brain

Given that it does it's identification by looking at the brain, whatever the cause is, it is ALSO manifested as a "difference in brain organization".

>That said I'm surprised that we can't tell men and women apart from the brain.

Who said we can't? The article points to that we can.

And there are other brain attributes besides organization we can use to tell them apart, the biggest being size, including size of certain structures.

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> Given that it does it's identification by looking at the brain, whatever the cause is, it is ALSO manifested as a "difference in brain organization".

I think the person you’re responding to is talking about confounding factors _outside_ the brain scan, like when a model that could identify skin cancer used the presence of a ruler as its most weighted input: https://venturebeat.com/business/when-ai-flags-the-ruler-not...

This is a huge problem in medical use for AI - you have non-technical medical professionals influencing the data used to train the model, and introducing biases in the data that the model is learning from.

>I think the person you’re responding to is talking about confounding factors _outside_ the brain scan, like when a model that could identify skin cancer used the presence of a ruler as its most weighted input

Well, those are just "bugs" and the results are then useless.

My point is that results taking into account only the scan (not random correlations with outside factors), would indeed be able to prove differences between M&F brains, without needing to also give a mechanism for it.

Some silly examples of stuff it might find that aren't actually brain differences:

1. There's an M/F letter or other identifying text on the scans 2. Men and women get put into the machine slightly differently, and the ai sees a slight difference in the pose of the scan 3. It sees something else that's identifying and pretty good at splitting, like ear holes for ear rings

I remember reading about one of the skin cancer finding ML models that was developed. Most of the pictures from malignant moles were taken from a specific office and the algorithm was picking up on the lighting in that room rather than other differences in the mole to determine likelihood of it being cancerous. It did a great job of identifying photos based on the type of lighting used, but was overall less effective at predicting cancer.

I’m reminded of the tale of a similar breakthrough, and upon ablation, it was found to be indexing on a particular artifact found on one X-ray machine. Or maybe the patient name?

Anyways, would recommend some caution, there’s no reason to believe there’s some obvious fundamental difference in brain organization that we can’t see ourselves, until the research is a bit further along :)

AI research is old. There's an (apocryphal?) 30 year old tale about using computer vision to detect tanks.

All the photos of tanks had clouds in the sky. And few to none of the counter examples had clouds. So darpa paid for an expensive cloud detector.

Without more information about the study, I'm guessing there's a 'M' or 'F' stamped on the image somewhere.

_edit_ Ah - https://gwern.net/tank the tank story

Unfortunately, these things can be extremely subtle. Far too often it boils down to sampling bias where the differences are actually differences in the variance estimation that results in a significant result. For example suppose that "male" dice are biased to role a 5 slightly more often than "female" dice. You will find a statistically significant difference related to the 5-side of the dice if you roll them enough. It doesn't mean that rolling a 5 indicates anything about the "gender" of a particular dice.

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