| > I seriously question what is the true motivation behind this over-stated agenda and have many answers as to why it exists and why it is so heavily funded/spotlighted. First, you could say the same thing for all AI research at the moment! Grandiosity is perhaps even more common in subcommunities of AI that aren't safety focused. Aside from grandiosity (either opportunistic or sincere), I don't think there's any sinister motivation. More importantly, I don't think the safety push is misplaced. Even if the current round of progress on deep (reinforcement) learning stays sufficiently "weak", the safety question for resulting systems is still extremely important. Advanced driver assist/self-driving, advanced manufacturing automation, crime prediction for everything from law enforcement to auto insurance... these are all domains where 1) modern AI algorithms are likely to be deployed in the coming decade, and 2) where some notion of safety or value alignment is an extremely important functional requirement. > ...and has, from what I can see, nothing to do w/ AGI nor are the approaches compatible In terms of characterizing current AI safety research as AGI safety research? Well, there is a fundamental assumption that AGI will be born out of the current hot topics in AI research (ML and especially RL). IMO that's a bit over-optimistic. But I tend to be a pessimist. > ...principal ideology... As an aside, I'm not sure what this means. |
What easily breaks this down is the depth and breath of the research effort vs. that of the productization and commercialization effort. As for research, the only thing that is required is a computer, power, an internet connection. Again, this breaks down the vast majority of the grandiosity and carves out one's true motivations.
> More importantly, I don't think the safety push is misplaced. Here's how I saw it some years ago... You can beat your head against the wall and create frankenstein amalgamations of ever evolving puzzle pieces that you will require expensive and highly skilled labor to make sense of with an end product being an overhyped optimization algo with programatic policy/steering/safety mechanisms.. Or you can clearly recognize and admit the possible foundation of it is flawed and start from scratch and work towards What is Intelligence and how to craft it into a computational system the right way. The former gets you millions if not billions of dollars, a career, recognition and a cushy job in the near term but will slowly lock you out from the fundamental stuff in the long term. The later pursuit could possibly result in nothing but if uncovered could change the world including nullifying the need of tons of highly paid labor to do development for it. Everyone in the industry wants to convince their investors the prior approach can iterate to the later but they know in their heats it can't (Shhh! don't tell anyone). So, the question for an individual is how aware and honest are they with themselves and what is their true motivation. You can put on a show and fool lots of people but you ultimately know what games you're playing and what shortfalls will result.
> Well, there is a fundamental assumption that AGI will be born out of the current hot topics in AI research (ML and especially RL). Quite convenient for those cashing in on the low hanging fruit who would like investors to extend their present success into far off horizons.
> As an aside, I'm not sure what this means. It means the thinking that weak AI is centered on could cause one to be locked out from perceiving that of AGI. It means : https://www.axios.com/artificial-intelligence-pioneer-says-w... But everyone is convinced they don't have to and can extend/pretend their way into AGI.