I used that as a singular example of how AI is actually not doing as good a job with diagnostics in medicine as articles appear to portray but you should probably read the link I linked as well as the one at the bottom of this comment.
In using AI to augment medical diagnostics we are literally seeing a decline in the abilities of diagnosticians. That means doctors are becoming worse at doing the job they are trained to do which is dangerous because it means they (the people most likely to be able to quality assure the results the AI spits out) are becoming less able to act as a check and balance against AI when it's being used.
This isn't meant to be an attack on the tool, just to point out that the use cases of these AI in medical fields are also being exaggerated or misrepresented and nobody seems to be paying attention to that part.
I would also caution you to ask yourself whether or not everyone being screened in this way would be a detriment by causing more work for doctors who's workloads are already astronomical for a lot of false positive results.
I understand that that may seem like a better result in the long run because it means more people may have their medical conditions caught earlier which lead to better treatment outcomes. But that isn't a guarantee, and it may also lead to worse outcomes, especially if the decline in diagnostic ability in doctors continues or increases.
What happens when the AI and the doctor both get it wrong?
https://hms.harvard.edu/news/researchers-discover-bias-ai-models-analyze-pathology-samples