This is a little odd: computer scientists are mathematicians, not scientists: therein lies the issue.

I think the more this is really absorbed, the clearer things become.

* Why are ai models of intelligence logical and not dynamical?

* Why are models rules of association, rather than interpretative frameworks?

* Why is a statistical association deployed without empirical verification?

* Why arent empirical (& verifiable) criteria given against predictive systems?

* Against the mechanisms of these systems?

* Why is ML an experimental discipline without experimental tests?

* Why doesn't ML research employ tests of significance?

* Why is the ability to experiment seen as incidental to intelligence?

* Why is ML sold with a scientific technical vocabulary whose meaning is given metaphorically?

* Why arent ML researchers aware these are metaphors?

* Why aren't scientists of intelligence researcher reviewing and informing the claims of the artificial intelligence community?

* Why do some of the most prominent "scientists" in the world advocate that understanding the world is a matter of mining datasets?

* Why don't these scientists defend the need for actual science in producing accurate models of reality?

* Why aren't computer scientists more sceptical?