> 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.
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.