I wonder how the false positive/false negative rates for this tool compare to that of a trained human. At some point we may reach parity, in which case what's the harm of trusting the automated result?
I don't think that a human reader in the loop will be going away for a long time. Sure, they can be at parity, but does a combined read have better results? This is an active research question.
I think what will happen is that over time, human interpreters and AI systems will "co-evolve" in a sense, where people will pick up on where models are wrong and also learn how to use models to understand their own blind spots. These are also active research topics that are in their infancy.
EDIT: To be clear, I believe that this is a different group of authors from coolwulf. Pubmed link: