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Safety has become a convoluted term for pseudo control over unintelligent and unpredictable Weak AI. The safety problem as it is framed in its current state cen

Safety has become a convoluted term for pseudo control over unintelligent and unpredictable Weak AI. The safety problem as it is framed in its current state centers on principal ideology for Weak AI and has, from what I can see, nothing to do w/ AGI nor are the approaches compatible. 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.

throwawayjava 8y ago
> 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.
- s1dechnl 8y ago
  Profit seeking. Career building. Fame and prominence aren't sinister. Instead they are common human motivation. Common enough to easily group a significant portion of the Grandiosity centered around 'AI'. 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-we-need-to-start-over-1513305524-f619efbd-9db0-4947-a9b2-7a4c310a28fe.html 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.
  - throwawayjava 8y ago
    I don't think the tenor of your post is very fair. > Again, this breaks down the vast majority of the grandiosity and carves out one's true motivations... 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. The rest of my post is a response to this sentiment. > As for research, the only thing that is required is a computer, power, an internet connection. All that's necessary for world-shattering mathematics research is a pen and paper. But still, most of the best mathematicians work hard to surround themselves by other brilliant people. Which, in practice, means taking "cushy" positions in the labs/universities/companies where brilliant people tend to congregate. Maybe most great mathematicians don't purely maximize for income. But then, I doubt OpenAI is paying as well as the hedge funds that would love to slurp up this talent! So people working on safe AI at places like OpenAI cannot be fairly criticized. They're comfortable but clearly value working on interesting problems and are motivated by something other than (or in addition to) pure greed/comfort. > Profit seeking. Career building. Fame and prominence aren't sinister. Instead they are common human motivation. Common enough to easily group a significant portion of the Grandiosity centered around 'AI'. So what? None of these motivations necessarily preclude doing good science. Some of those are even strong motivators for great science! The history of science contains a diverse pantheon of personality types. Not every great scientist/mathematician was a lone genius pure in heart. In fact, most were far more pedestrian personalities. The "pious monk of science" mythology is actively harmful toward young scientists for two reasons. First, the ethos tends to drive students away from practical problems. Sometimes that's ok, but it's just as often harmful (from a purely scientific perspective). Second, this mythology has significant personal cost. More young scientists must realize that it is possible to make significant contributions toward human knowledge while making good money, building a strong reputation, and having a healthy personal life. Maybe then we'd have more people doing science for a lifetime instead of flaming out after 5-10 years. > It means the thinking that weak AI is centered on could cause one to be locked out from perceiving that of AGI. Thanks for the clarification!

throwawayjava 8y ago

> 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.

s1dechnl 8y ago
Profit seeking. Career building. Fame and prominence aren't sinister. Instead they are common human motivation. Common enough to easily group a significant portion of the Grandiosity centered around 'AI'. 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-we-need-to-start-over-1513305524-f619efbd-9db0-4947-a9b2-7a4c310a28fe.html 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.
- throwawayjava 8y ago
  I don't think the tenor of your post is very fair. > Again, this breaks down the vast majority of the grandiosity and carves out one's true motivations... 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. The rest of my post is a response to this sentiment. > As for research, the only thing that is required is a computer, power, an internet connection. All that's necessary for world-shattering mathematics research is a pen and paper. But still, most of the best mathematicians work hard to surround themselves by other brilliant people. Which, in practice, means taking "cushy" positions in the labs/universities/companies where brilliant people tend to congregate. Maybe most great mathematicians don't purely maximize for income. But then, I doubt OpenAI is paying as well as the hedge funds that would love to slurp up this talent! So people working on safe AI at places like OpenAI cannot be fairly criticized. They're comfortable but clearly value working on interesting problems and are motivated by something other than (or in addition to) pure greed/comfort. > Profit seeking. Career building. Fame and prominence aren't sinister. Instead they are common human motivation. Common enough to easily group a significant portion of the Grandiosity centered around 'AI'. So what? None of these motivations necessarily preclude doing good science. Some of those are even strong motivators for great science! The history of science contains a diverse pantheon of personality types. Not every great scientist/mathematician was a lone genius pure in heart. In fact, most were far more pedestrian personalities. The "pious monk of science" mythology is actively harmful toward young scientists for two reasons. First, the ethos tends to drive students away from practical problems. Sometimes that's ok, but it's just as often harmful (from a purely scientific perspective). Second, this mythology has significant personal cost. More young scientists must realize that it is possible to make significant contributions toward human knowledge while making good money, building a strong reputation, and having a healthy personal life. Maybe then we'd have more people doing science for a lifetime instead of flaming out after 5-10 years. > It means the thinking that weak AI is centered on could cause one to be locked out from perceiving that of AGI. Thanks for the clarification!