Working in the ML space myself I try to tell my peers to think deep about their work and the consequences. Not just for ethics, but because it helps you do better.

So far I get a lot of pushback and statements like "it's just linear algebra" and "quality doesn't matter, it's quantity. Just scale. That's the bitter lesson". The former tells me they know very little linear algebra and the latter tells me they know very little about probability distribution and the concept of coverage... I routinely see papers get awards and tens of thousands of citations when they're making errors I would expect undergrads in my classes to do better at... I think a big reason I'm frustrated is that supposedly we share the same goals -- building AGI -- but I'm told I'm stopping them from doing so while they reject my papers and theirs gets accepted... (Fwiw I'm happy to accept scale papers. There should be a wide range of ideas explored. But I'm upset that we're on a railroad and any deviation from that is considered heresy)