There's a "trust but verify" element of airplane automation that is ingrained in you as a pilot. The ML aspect of self-driving cars generally make it a lot less easy to reason about and predict. That's problem 1. Problem 2 is then speed; Even in the airline world, there are published minimums at which pilots need to be absolute certain that the AP is doing the right thing before they commit to land, even in cases where the autopilot is responsible for the entire landing (Autoland is a capability that a lot of airliners have had for many decades).
What we're talking about here is several seconds heads-up with visual AND instrument confirmation, that the computers are doing what they're supposed to before we allow the plane to land. Not only that, but we bend over backwards ensuring that there is all kinds of redundancy and procedures in place to ensure the accuracy of the system: Multiple instruments using different kinds of technologies confirming one another, greater separation between aircraft to guarantee ILS radio beacon accuracy, etc. Conversely, in the self-driving world, we're having these ML algorithms make split-second decisions with no real way of informing the driver what it is basing it on in an environment that is far less predictable and constantly-changing with someone who is not a professional behind the wheel.