I think you're generalizing too much.
These are AI/ML researchers, and so you can probably talk about that area at Meta, but it doesn't apply to other departments necessarily.
But I think it's kind of obvious that AI/ML is a dicey proposition there. See for example[0] how they decided to stop doing facial recognition. I can easily imagine a lot of AI projects being canned or back-burnered like that now. What's ML used for at Meta? Feed recommendations, social graph inferences, face identification, etc? All those are under heavy scrutiny, and a lot of the work of doing it "right" is not even an ML question at all, but one of policy, regulation, and product. It's not like self-driving cars where people can generally agree that "getting from A to B without crashing" is a good thing, and where the obvious ML and engineering problems line up with product problems. But if you "increase engagement" with your feed recommendations, that could be good or bad in ways that ML can't really tell you. If you get better at identifying people in pictures, people are going to hate you and there will news articles about stalking. If you identify who a potential friend might be, that's a privacy consideration, etc, etc.
But what's going on there is pretty independent of the "metaverse" stuff, I think.
[0] https://news.ycombinator.com/item?id=29084081
These are AI/ML researchers, and so you can probably talk about that area at Meta, but it doesn't apply to other departments necessarily.
But I think it's kind of obvious that AI/ML is a dicey proposition there. See for example[0] how they decided to stop doing facial recognition. I can easily imagine a lot of AI projects being canned or back-burnered like that now. What's ML used for at Meta? Feed recommendations, social graph inferences, face identification, etc? All those are under heavy scrutiny, and a lot of the work of doing it "right" is not even an ML question at all, but one of policy, regulation, and product. It's not like self-driving cars where people can generally agree that "getting from A to B without crashing" is a good thing, and where the obvious ML and engineering problems line up with product problems. But if you "increase engagement" with your feed recommendations, that could be good or bad in ways that ML can't really tell you. If you get better at identifying people in pictures, people are going to hate you and there will news articles about stalking. If you identify who a potential friend might be, that's a privacy consideration, etc, etc.
But what's going on there is pretty independent of the "metaverse" stuff, I think.
[0] https://news.ycombinator.com/item?id=29084081