I think that Dreyfus has unfortunately set back the cultural understanding of computers by decades, by confidently declaring certain tasks impossible for computers to do, because minds have "insight" or "tacit knowledge" or are "holistic", each of which functionally lets a mind be a ghost in the machine.
A lot of the rhetorical momentum comes from pointing at the progress of technology at various stages in human history, especially the fits and starts of AI/Language research in the mid 20th century, and remarking at how little progress has been made.
And the terms used to define how computers were are also vague.
>Given the nature of inference engines, AI's representations must be formal ones
When AI trained on images of dog faces "dreams" on an image, and progressively twists flowers and purses into dog faces and noses, is the connection made between patterns and dog faces "formal" ? Are the images generated by ThisPersonDoesNotExist informal? The ways computers work on data now deals with abstractions & fuzziness in a way that I think Dreyfus did not imagine to be possible. I think Dreyfus wanted to say that the higher-level methods that we now employ to generate images, human-like language, transpose art styles and create nearly photorealistic faces are on a foundation of principles that are new and distinct from the characteristic principles that he understood to be central to computing. But all of our new progress is implemented on a foundation of silicon and bits, too, which simulate neural networks, meaning those are just as computational as the desktop calculator app. I think Dreyfus just couldn't imagine that 'computing' could include all this extra stuff, and, to take a term from Dennet, Dreyfus mistook his failure of imagination for an insight into necessity.