Im struggling to understand how this is is different from “we will build aligned ai to align ai”. specifically: Can someone explain to me how human-like and AGI are different? Can someone explain to me why human-like AI avoids typical x-risk scenarios (given those human-likes could say clone themselves, speed up themselves and rewrite their own software and easily become unbounded)? Why isnt an emulated cognitive system a real cognitive system… i don’t understand how you can emulate a human-like intelligence and it not be the same as fully human-like.
currently my reading of this is we will build human-like AI because humans are bounded so it will be too, those bounds are: (1) sufffiecent to prevent xrisk (2) helpful for (and maybe even the reason for) alignment. Isnt a big wide open unsolved part of the alignment problem “how do we keep itelligent systems bounded”? What am I missing here?
I guess one maybe supplementary question as well is: how is this different from normal NLP capabilities research which is fundamentally about developing and understanding the limitations of human like intelligence? Most folks in the field say who publish in ACL conferences would explicitly think of this as what they are doing and not trying to build anything more capable than humans.
Im struggling to understand how this is is different from “we will build aligned ai to align ai”. specifically: Can someone explain to me how human-like and AGI are different? Can someone explain to me why human-like AI avoids typical x-risk scenarios (given those human-likes could say clone themselves, speed up themselves and rewrite their own software and easily become unbounded)? Why isnt an emulated cognitive system a real cognitive system… i don’t understand how you can emulate a human-like intelligence and it not be the same as fully human-like.
currently my reading of this is we will build human-like AI because humans are bounded so it will be too, those bounds are: (1) sufffiecent to prevent xrisk (2) helpful for (and maybe even the reason for) alignment. Isnt a big wide open unsolved part of the alignment problem “how do we keep itelligent systems bounded”? What am I missing here?
I guess one maybe supplementary question as well is: how is this different from normal NLP capabilities research which is fundamentally about developing and understanding the limitations of human like intelligence? Most folks in the field say who publish in ACL conferences would explicitly think of this as what they are doing and not trying to build anything more capable than humans.