This sounds like a loaded question but... Why don't more people who talk about AI $subject (eg, ethics, policy, strategy) actually engage with foundational technical literature? What is the plausible justification for not habitually skimming Arxiv?
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An amusing test reporters could apply: "Oh, before we begin, would you mind quickly writing down the equations describing backprop in, say, a simple feedforward net? Okay if it's a bit rough!" AKA, do you know how any of this works?
Slightly unfair - there are people with interesting things to say who would fail this test. Still, I think the idea has merit, some kind of FizzBuzz for AI "experts".
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I think I might fail this test, but I think I could explain, say, backprop in a way that made sense to them, then connect that to interesting innovations eg resnets, skip gates, etc, and tie this to progress in image recognition as a whole. (And that feels like it'd be useful)
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It's not meant seriously (though something similar in spirit might be useful). I certainly think you should be talking to reporters! Didn't mean to imply otherwise.
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A serious point: the notion of an "AI expert" is a very difficult one. Does it mean an expert on: (a) hypothetical future artificial intelligences; or (b) the current crop of techniques, which may or may not have anything to do with (a), but are certainly far distant from it.
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I didn't say expert in my original thing. I think experts get annointed by the press/participants in discourse. So people can usually talk their way into becoming 'experts'
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Also because people think of AI as specific things, e.g. backprop while there are huge chunks of AI that have nothing to do with such methods. The answer to the OP question imho is that AI is an abstract notion and encompasses ethics in CS in general.
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E.g. Evrn if you do simple if then else algorithms for something that deals with human your choice of what goes within there still is a matter of ethics but has little to do with how GRUs are trained.
End of conversation
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important for people to identify their expertise and note how it's applied, so ex: an ethics phd can say interesting things about quantum computing w/o reading arxiv, but burden is on them to identify how their expertise being applied, not claim qc expertise
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