I mostly agree, except for the idea that instructions “cannot be ambiguous in any way”. I think this is more of a nuance than anything, however. I think the di

I mostly agree, except for the idea that instructions “cannot be ambiguous in any way”. I think this is more of a nuance than anything, however. I think the difficulty of the nuance is that we usually don’t realize when our language is ambiguous. Handwriting recognition is a super ambiguous problem, despite being easily solved with great accuracy today: good luck formalizing how it’s actually done and explaining it to a layperson. The difficulty in most non-trivial AI/ML tasks is in figuring out how to structure the problem (for handwriting recognition, let’s not forget that we have the tremendous benefit of hindsight), which essentially amounts to deciding that some kinds of ambiguity are okay (eg.: things that can be reduced to a statistical or classification problem), and some kinds of ambiguity need to be resolved (eg.: avoiding potholes is probably a good idea, and one way or another this has to be rewarded or encoded, by some mechanism… and great care is required to account for basically everything you’d expect to find in a really good driving manual). There are some types of ambiguities that AI/ML are very good at… But to your point, there is a degree of “relative unambiguity” that is required. The difficulty is compounded by human biases too: what is obviously-unclear to a careful observer might appear to be super clear to an overconfident person.