How could you tell the difference between people who genuinely believe and people who genuinely believe because bad? Have you considered that where you fall on this question might be because of some pre-existing assumptions?
You could be right but it also doesn't have to be a corporate psyop. It could be experts in the industry raising some sincerely held criticisms and people at large being like, "oh that's a good point." Even if we're in the latter case they're also allowed to be allowed to be wrong or just misguided.
You don't actually to attack the intent of the speaker in this case, you could just be like, "here's why your wrong."
There is nothing to suggest that these are experts. The names in question have been so focused on researching AI tech throughout their career that it is highly unlikely that they have any expertise in subject matter we are discussing. There is only so much time in the day.
I mean, they are clearly experts in AI technology, but that is unrelated to being an expert in social and humanitarian issues. That is a completely different field of study. There is no doubt someone out there who is an expert in that, but I don't think you will find overlap with expertise in AI systems. Again, there is only so much time in the day. It is not practical to dive that deep into different subjects like that at the same time.
Hinton, at least, seems to have backed away from AI to work on becoming an expert in social and humanitarian issues. Perhaps someday, with enough dedication, he will get there. But that journey only just began a few months ago. Becoming an expert doesn't happen overnight like that. It takes time.
You could be right but it also doesn't have to be a corporate psyop. It could be experts in the industry raising some sincerely held criticisms and people at large being like, "oh that's a good point." Even if we're in the latter case they're also allowed to be allowed to be wrong or just misguided.
You don't actually to attack the intent of the speaker in this case, you could just be like, "here's why your wrong."