Not to be rude, but of the active AI researchers I've seen state an opinion, almost all of them are critical of the Bostrom book, with the main critique being (iirc) that rapid/exponential self improvement is presented as an inevitability when there is very little reason to think that this is the case.

Not to say that Superintelligence isn't worth reading (as you say, it's a pretty enjoyable book), but I think it's important to point out that Bostrom's views are not broadly accepted by the people actually writing ML/AI code.

The primary concerns I've seen from the community are

a) issues with research itself (lots of derivative/incremental/epicycle-adding works with precious few lasting improvements)

b) issues with ethics (ML models propagating bias in their training data; ML models being used to violate privacy/anonymity)

c) issues with public perception/presentation (any ML/AI tech today is usually incredibly specialized, built to solve a single specific problem, but journalists and people pitching AI startups frequently represent AI as general-purpose magic that gains new capabilities with minimal human intervention).