I understand that those are the takeaways, but where is the evidence? The author just jumps to some vaguely related topics as if it's evidence, while what he's really doing is spinning some kind of narrative, and the narrative is wrong.

About the takeaways:

1. As I explained in my comment, this is not true.
2. Who thinks that way? Everybody I know, both laymen and people in the field of Data Science and Machine Learning, have healthy skepticism of AI.
3. Having worked as a data scientist, I can attest that data scientists check their algorithms, use common sense, and put an emphasis on understanding their data.

Honestly,the article just reads to me as a boomer theory-focused economist who's upset of the turn towards quantitative and statistics-heavy approach that his field has taken. There is a certain (old) school of economists who prefer theoretical models and takes a rationalist over an empirical approach. The problem with their approach is that the theoretical models they build use assumptions that often turn out to be wrong. They use "common sense" rather than relying on data but the world is complex and many "common sense" assumptions don't actually hold.