False positive diagnoses cause a huge amount of patient harm. New technologies should only be deployed on a widespread basis when they are justified based on solid evidence-based medicine criteria.
No one says you have to use the AI models stupidly.
If it works poorly for black women and female women dont use it for them.
Or simply dont use it for the initial diagnosis. Use it after the normal diagnosis process as more of a validation step.
Anyways, this all points to the need to capture biological information as input or even having seperately models tuned to different factors.
Every single AI company says you should use AI models stupidly. Replacing experts is the whole selling point.
OK so should we optimize for blindly listening to AI companies then?
We should assume people will use tools in the manner that they have been sold those tools yes.
But these tools include research like this. This research is sold as proof that AI models have problems with bias. So by your reasoning I'd expect doctors to be wary of AI models.
The guidelines on how to use a particular AI model can only be written after extensive clinical research and data analysis. You can't skip that step without endangering patients, and it will take years to do properly for each one.
> having seperately models tuned to different factors.
Sure. Separate but equal, presumably.
Whats the alternative? Withholding effective tools because they arent effective for everyone? One model thats worse for everyone?
This is what personalized medicine is, and it gets more individualistic than simply classifying people by race and gender. There are a lot of medical gains to be made here.
I'm not arguing against using the models per se. It's just that this is a social problem, to which there's no good technical solution. The hard road of social change is the only real alternative.
Citation needed. Personalized medicine seems like a great idea in principle, but so far attempts to put it into practice have been underwhelming in terms of improved patient outcomes. You seem to be assuming that these tools actually are effective, but generally that remains unproven.