I find the radiologist use case an illuminating one for the adoption of AI across business today. My takeaway is that when the tools get better, radiologists aren't replaced, but take up other important tasks that sometimes become second nature when reads (unassisted) are the primary goal.

  In particular, doctors appear to defer excessively to assistive AI tools in clinical settings in a way that they do not in lab settings. They did this even with much more primitive tools than we have today... The gap was largest when computer aids failed to recognize the malignancy itself; many doctors seemed to treat an absence of prompts as reassurance that a film was clean

Reminds me of the "slop" discussions happening right now. When the tools seem good, but aren't, we develop a reliance to false negatives, e.g. text that clearly "feels" written by a GPT model.