[psoy]

The inference-based methods in AI qre more likely to he of the "probabilistic graphical models" variety (there are already marriages of Bayesian and Deep Learning techniques), and less likely to be of the "first order predicate calculus" variety. We humans don't have a particularly strong logical inference engine either - unless properly trained, people make the silliest logical mistakes and arrive at wrong conclusions all the time.

[Chabsff]

Right, I meant "prolog-style formal inference engine". My point is that this "human imperfection" also present in probabilistic engines have artifacts that are fundamentally at odds with many business requirements where we are attempting to shoehorn then.

It's almost more of a cultural issue than a technical one. The level of explainability currently desired from automated systems is possibly not achievable, simply because we want to uphold them to a different standard.