In this case I think most jurisdictions would treat the AI as just another tool or piece of equipment.

If you asked a similar question about who would take the blame if a piece of X-ray equipment was not working properly and caused some form of harm, the liability might fall on the X-ray machine manufacturer who guaranteed a certain level of accuracy, or it might fall on the hospital that procured the (potentially unsafe/certified) equipment. It might also fall on the physician who wasn't following the proper protocol for using the equipment.

I'm working on this full-time. We sell our model as a pre-diagnosis tool. We tune the parameters to ensure low false negatives (less than human doctor), though the false positives are higher. However, it whittles down the queue substantially. For non-clinical uses, depending on your use case, you can actually skip the negatives designated by the model. For clinical use cases, you might use it to prioritize your read queue and/or highlight areas of interest.

Feel free to reach out to me if you are curious. I can talk in great detail.

BTW, you can purchase insurance for activities like these, though I cannot say I've seen a legal case yet, so I dont know exactly how it would work out.

This is why these tools are generally described as "decision support" systems and not "diagnostics" systems. There are many reasons why you don't want to be classified as a diagnosis device (FDA approval is a big one), but ultimately letting the doctor make the final decision removes the ML controversy out of the picture.

EDIT, for context: https://en.wikipedia.org/wiki/Clinical_decision_support_syst...

The commercial entity backing the ML program should be responsible. If one doesn't exist then the comparison fails, as one would presumably not be willing to trust the competency of a public domain ML program without a true, commercially and medically backed "second" opinion (algorithmic or otherwise).

Perhaps one day, ML programs running eye diagnostics will be as cheap and disposable to use as pregnancy stick tests: "Point and diagnose."

If a doctor misdiangosis someone based on an outside errant lab test, what happens?

I think the situations would be viewed identically. I don't know the exact processes, but lots of documentation would go into it and if the lab that gave the errant lab test has a history of poor results, they may get investigated and closed down.

If this was a one-off error, that will get chalked up to a one-off error. Even if the patient dies.

The AI program would say "I think there is a 99% chance you have this eye ailment."

If that turns out to be wrong, the programmer will just point to the other 99 people successfully treated and shrug.

If a car has to decide between killing ...

The trolley problem: https://www.youtube.com/watch?v=21EiKfQYZXc&feature=youtu.be...