It is true that ML algorithms are almost always trained on radiologist labels on the same modality, and thus take in the reader biases. I also agree that some radiologists are better than others as you imply.
As a patient, one does not know who will read their film. IMHO we as an industry should aim not at beating 99.999% of radiologists. We should merely make products which consistently perform not worse than an average radiologist at a particular institution. It is always thrilling to outperform humans with your software, but at the end patient outcomes are what matters. Those are about consistent performance over a long period of time.
Demonstrating this consistent performance is the challenging part, but it is possible to prove it through sufficiently careful and lengthy prospective trials. That’s what we are focusing on, and I would love to see the other players in the industry do the same.