I think there's lots of work to be done in quantifying and comparing discrepencies and lack of confidence in neural net classifications and sensor/model outputs

I think there's lots of work to be done in quantifying and comparing discrepencies and lack of confidence in neural net classifications and sensor/model outputs. Part of this is human interface design. An example of this is the "sensor disagree" light on the Boeing 737 max (which unfortunately was optional equipment not installed for the Ethiopian Airlines 737 Max crash), although I do believe we can do much better than a mere light. A full screen and a sound system with over-the-air updates means we ought to be able to field a really good (and continuously improving) system for communicating when the autopilot's sensors disagree or if the model has low confidence. This is likely going to take years or even decades of operational use over millions of vehicles to refine with good confidence.