ok, maybe it's an US specific thing, why wouldn't a clinical radiologist have all the information he can gather about his patient including race to help the diagnosis?
Because in the US we are required to pretend that there is no such thing as race and no such thing as gender, and all people are exactly and precisely the same and there can be no differences.
Not to get into a flame war, but I want to present an alternate option to yours.
Because in the US some people have a hard time understanding that all races and genders deserve to be treated equally as humans with the same access to goods and services. Further, that there are disparities in care based on race/ethnicity[1][2] and gender[3][4] because of that racism/sexism present in the systems. This then leads to requiring that race/ethnicity and gender data be scrubbed sometimes to keep people from impacting outcomes based on their own biases.
It sometimes makes sense to scrub race/ethnicity/gender information from certain types of data, typically when a human is going to be making individual decisions.
For example, not having race data on resumes is generally productive, because that categorization can't provide a meaningful input to the decision associated with an individual person. Even if it were to be the case that there was some correlation between race and skill at whatever job you're interviewing for[1], the size of the effect is almost certainly small, and in the meanwhile you've also controlled for any bias in the person doing the reviewing.
If you're having a machine look at a dataset, and the machine determines that race or ethnicity is a material factor in determining some attribute in that dataset, you're not doing anybody any good by denying that fact and destroying the result.
[1]Let's ignore for the purposes of this discussion, fields (like certain sports) where extreme competition combines with a position heavily dependent upon racially-linked physical characteristics. Though even in this case, there is still a (different, weaker) argument for suppressing race data in "resumes" (yes, I know, ballplayers don't submit resumes to their local NBA franchise)
Race is a rough, subjective, culturally-bound summary of characteristics. If you're already evaluating characteristics, adding either your guess of race or a self-reported race is like injecting gossip into good data.
If the outcome that you're trying to predict is also affected by perceptions of race, you've built a gossip feedback loop.
Then you should be looking at ethnicity and not "race" as such. For example, Ashkenazi Jews as an ethnic group are genetically very distinct from other Europeans, but are generally considered "white" on self-reported race surveys.
Now look just above that latter table, showing distances between East Asians and Europeans. The distances are far greater--more than 10x.
The precision with which we can identify and track ancestry, often based on small fractions of DNA (Y-chromosome in particular wrt Ashkenazi Jews, not mtDNA as one might think) doesn't imply the degree of genetic distinctiveness.
>If you're having a machine look at a dataset, and the machine determines that race or ethnicity is a material factor in determining some attribute in that dataset...
I think the trickiness is in providing the machine unbiased data to begin with so that it doesn't incorrect associations between features like race. The most egregious examples I'm aware of are the machine learning systems used to suggest criminal sentencing, but, apropos to this topic I believe there are cases where it may produce erroneous associations in something like skin cancer risk.
>> Because in the US we are required to pretend that there is no such thing as race
Then you are not pretending very well. When I lived in the US I was shocked at how often it was an issue. It permeates nearly every aspect of US culture.
The icing on that cake: A government-run interactive map so you can lookup which races live in which neighborhoods. Some versions allow you to zoom in to see little dots representing clusters of black or white residents.
https://www.census.gov/library/visualizations/2021/geo/demog...
Actually, the US federal government specifically recommends that healthcare providers record patients' race, ethnicity, assigned sex, and gender identity. Most of those elements are self identified.