Expanding on this, particularly regarding causal reasoning and rules, what I find especially puzzling is the desire to apply deep learning even in cases where the rules are explicitly known already, and the actual challenge would have been to reliably automate the application of the known, explicitly available rules.

Such cases include for example the application of tax law: Yes, it is complex and maybe cannot be automated entirely. However, even today, computer programs handle a large percentage of the arising cases automatically in many governments, and these programs often already have automated mechanisms to delegate a certain percentage of (randomly chosen, maybe weighted according to certain criteria) cases to humans for manual assessment and quality checks, also a case of rule-based reasoning. Even fraud detection can likely be better automated by encoding and applying the rules that auditors already use to detect suspicious cases.

The issue today is that all these rules are hard-coded, and the programs need to be rewritten and redeployed every time the laws change.