[_0w8t]

I am referring to this fragment:

> Thus, for many applications, in order to successfully interact with humans, machines will need to explain their reasoning, including some quantification of confidence, to humans.

No doubtful there are cases when an explanation is easy. Often this is because we have a very solid model like physics of a car. In fact since we know the model, we do not need an explanation, we must demand that the algorithm follows the model or declare it unfit.

But how can we expect an explanation for a behavior in a critical situation on a road that was not explicitly programmed and when the algorithm decided to turn to a particular degree bases on a non-trivial inference? Similarly, when an algorithm decides if a patient needs an emergency operation or if they can wait, why can we expect an simple explanation especially for the patient with rare conditions when algorithm again must perform an inference, not a deduction from 1000 very similar cases?

[jupiter90000]

Maybe you couldn't always expect an explanation, but having one would certainly be useful. Methods that could get the job done while also providing enough information to explain or at least shed some kind of light on why the solution was chosen would likely be preferable.