I think the type of explainability Yann LeCun is describing in this post is not the same as what people really want when they talk about explainable AI. To use

I think the type of explainability Yann LeCun is describing in this post is not the same as what people really want when they talk about explainable AI. To use his example, I think most people would be fine with an AI that said "we're doing X because that's what heuristic Y prescribes for the situation", and getting from where we are now to something like that is the challenge. FWIW i see a similar dialogue in biomedical contexts quite a bit, where there's some cool but hard-to-trust work being done in data-driven image restoration (https://www.biorxiv.org/content/10.1101/236463v5.abstract https://www.biorxiv.org/content/10.1101/236463v5.abstract). There's still a lot that could be done short of programs providing a priori mathematical proof for all models.