"How much does this input seem to confuse this output? What is the pattern across inputs for how this model is systematically confused?"
Causality -> counterfactuals
"How would the outcome be different if x was different? If I acted differently, would I get a more favorable outcome?"
You're right to say these are two different things. They are.
And they're different still from interpretability, i.e., "What are the explicit patterns that this model is seeking in the data?"
DL practitioners routinely mix up explainability and interpretability but I would never in a million years have seen LeCun be so intellectually dishonest as to lump causality in there with them.
The thing is, I would claim that causality, explainability and interpretability are all mixed together in human informal discussions of various phenomena. As others on the thread have pointed out, Pearl's causality isn't everyone's causality. A tension structure can disrupt our "common sense" idea of what's holding up what but tensions structure doesn't seem at all like a black-box, unexplainable item. The way the article mixes the range of these issues seems definitely wrong but I don't think that means the line between all things is normally crystal clear.
"How much does this input seem to confuse this output? What is the pattern across inputs for how this model is systematically confused?"
Causality -> counterfactuals
"How would the outcome be different if x was different? If I acted differently, would I get a more favorable outcome?"
You're right to say these are two different things. They are.
And they're different still from interpretability, i.e., "What are the explicit patterns that this model is seeking in the data?"
DL practitioners routinely mix up explainability and interpretability but I would never in a million years have seen LeCun be so intellectually dishonest as to lump causality in there with them.