4 ms·
Yep. Far more important to, 1 - get a result consistent with both reasonable diagnosis and standard of care for the condition in question. And, 2 - get the same
by bilbo0s 3y ago
Yep. Far more important to, 1 - get a result consistent with both reasonable diagnosis and standard of care for the condition in question. And, 2 - get the same result given the same input every time. The FDA doesn’t like when you say “amputate the left leg” one day, and then say “amputate the right leg” the next day. Particularly when that happens after you’ve already amputated the left leg and there was nothing wrong with it.
Believe it or not, that amputation scenario has happened before. It wasn’t with AI software, but rather imaging software that hosed an orthonormal conversion on a DICOM dataset. But the same rules should obviously apply to AI.
- RandomLensman 3y agoThis sounds a bit like using a standard manual (not the wrong leg part, though).
- bilbo0s 3y agoWell, they don’t generally think it’s necessary to put “don’t amputate the wrong leg” in the books in med school, but yes, if it helps to think of it that way, you can.
- rickdeckard 3y agoIn your leg-example your condition #2 was not met, let's imagine that still happens despite using "AI magic": At the point when "amputate the right leg" was found to be the correct diagnosis, an authority should be able to audit and reconstruct the wrong "amputate left leg" diagnosis, trace the root-cause of this decision and verify the corrective action. For this, it is important to be able to reconstruct the process of any computer-aided recommendation used. A corporate statement like "we don't know why the model recommended the left leg back then, now it correctly recommends the right leg when feeding the same data" should not be sufficient.