This article describes a new study using AI to identify sex differences in the brain with over 90% accuracy.
Key findings:
- An AI model successfully distinguished between male and female brains based on scans, suggesting inherent sex-based brain variations.
- The model focused on specific brain networks like the default mode, striatum, and limbic networks, potentially linked to cognitive functions and behaviors.
- These findings could lead to personalized medicine approaches by considering sex differences in developing treatments for brain disorders.
Additional points:
- The study may help settle a long-standing debate about the existence of reliable sex differences in the brain.
- Previous research failed to find consistent brain indicators of sex.
- Researchers emphasize that the study doesn’t explain the cause of these differences.
- The research team plans to make the AI model publicly available for further research on brain-behavior connections.
Overall, the study highlights the potential of AI in uncovering previously undetectable brain differences with potential implications for personalized medicine.
I would be curious what this would predict for trans (including those both on and off hormone therapy), intersex, or homosexual individuals. My guess is that at a minimum in those cases it’s accuracy of predicting either their gender or sex would be very poor, although it would be absolutely fascinating if it accurately predicted their gender rather than their sex. The opposite result (predicting sex but not gender) would also be interesting but less so.
I’d be very interested in those results too, though I’d want everyone to bear in mind the possibility that the brain could have many different “masculine” and “feminine” attributes that could be present in all sorts of mixtures when you range afield from whatever statistical clusterings there might be. I wouldn’t want to see a situation where a transgender person is denied care because an AI “read” them as cisgender.
In another comment in this thread I mentioned how men and women have different average heights, that would be a good analogy. There are short men and tall women, so you shouldn’t rely on just that.
I have a suspicion that this is exactly what’s going on here and may be why past studies found no differences. AI is much better at quickly synthesizing complex patterns into coherent categories than humans are.
Also, 90% is not that good all things considered. The brain is almost certainly a complex mix of features that defy black and white categorization.
Hopefully we will be wise enough to not require trans people to prove their trans-ness scientifically. People have a right to do what they wish with their bodies and express their gender in a way that feels right to them, and should not be required to match some artificial physical diagnosis of what it means to be trans. Even if it turns out that most trans people do share certain brain structures or patterns. There will always be exceptions and that doesn’t mean we get to label someone’s identity as inauthentic.
Given any finite data set above a trivially small size/complexity, and an undefined set of criteria, the odds of meaningless patterns appearing are extremely high.
Machine learning algorithms are basically automated P-hackers when misused. Be skeptical of any conclusions drawn from ML that are not otherwise verifiable.
Unlikely as it might be, maybe the 10% error rate is from gender queer people that haven’t realized/faced it yet.
There are a lot of potential explanations. In essence they built a model to categorize brain features into male and female, and then tested this against their label of male or female on each brain. So this could result from problems with the model predictions—or just as easily from their “correct” labeling of each brain as male or female.
So a big question is how did they define male and female? By genetics? By reproductive anatomy? By self reported identity? This information was not in the article. All of these things are very likely correlated with things happening in the brain, but probably not perfectly. It’s worth noting that many definitions of sex do not consider gender identity at all—if such a definition was used, then a trans-man might be labeled female in their data, whether they have reckoned with their identity or not.
I looked into this, the study analyzed three pre-existing fMRI datasets.
I wasn’t able to find any info on how these projects assessed sex/gender of participants.
Based on this, I’d assume they just used AGAB as that’s how medical professionals approach patients in their care.
Someone else mentioned the iris test being more accurate but that it also includes the eye area around the iris, including eyelashes and eye shape. That would clearly bias the model.
I wonder if there’s anything else that’s might be giving clues to the machine or if it I limited to what they say it’s determining sex based on. As a trans-nonbinary person myself, I’m very skeptical and anxious about technologies like this leading to biases and prejudices being emboldened.
I don’t think that’s a fair comparison. Height is a single value. If you trained an AI on that, it would be guessing. A brain has many, many more parameters to take into consideration when going into an artificial neural network.
That just makes my point stronger, though. The basic gist of what I was saying is that even if there is a statistical clustering of data into two groups that seem correlated with some category, that doesn’t mean that you can absolutely rely on that data to classify people into those categories.
The more data you have, the more confident you can be that the resulting categorisation is correct. If you’re saying this is incorrect, I disagree with you. If you’re saying absolute confidence that the categories themselves are correct is impossible, then I agree with you
Just a guess but if they labeled training data either male or female then i believe its more likely that it detects biological sex…
But if i they would also label and train on lgbt brains then i bet machine learning can differentiate between all of those.
I bet you can do the same thing with neurodivergent people but you would need to make sure the training data is without error to make me trust it.
Anecdotally, women develop language earlier than men as children.
The MtF trans person I know most closely was in the 90th percentile for their birth sex in early language development.
I suspect it might well show trans brain differences.
That’s interesting. I and my father are both hyperlexic (as in, taught ourselves to read, in my case, before I could speak) but not trans or autistic.
I wonder how that mixes into the fold?
I disagree. It could be wildly interesting if somebody born a male got a scan and it revealed a female brain. Dunno if “anti-trans” people would agree then that a sex-change is valid or if they’d disagree and start finding other excuses.
Assuming I’m understanding your point that would be a mis-categorization. I’m assuming you meant a straight non-trans male was scanned and the result predicted a female brain was scanned (a result matching neither the sex nor gender)? I was saying it would be less interesting if it scanned say a female-to-male trans person and returned a result of female (correctly guessing the sex but not the gender), than if it had returned a result of male (that is correctly guessing the gender but not the sex). It would also be interesting if it could detect trans people in general as their own unique group.
I do mean person born a male that wants to become female. Anti-trans people often make points that trans people are just forced into being trans by the trans-mafia (or whatever term they use) aka social pressure. A brain scan indicating a female brain would counter that. But as I said, they’d probably find other excuses “it’s a mental disease that can be treated” and so on and so forth.
That would embolden the anti-trans crowd.
Science is ongoing though, so who knows what the results will be.
Unfortunately no matter the outcome there’s likely danger there which is why legal protections are going to be critical. If it doesn’t accurately detect trans people they’d argue it’s evidence that being trans is a choice and that they could just decide to “be normal”. If it does accurately detect trans people in some ways that’s even more dangerous because now you’ve created a trans detector that could potentially be used to target people.
Ultimately from a scientific perspective there’s still so much we don’t know about how our brains work and even less known about how gender and sexual orientation are determined. Projects like this provide valuable clues about all of that, but there’s still so much that’s unknown that any result is potentially useful. I personally would find it more interesting though if it did accurately detect someone whose trans as it would suggest there’s physically detectable brain differences.