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I may have read too much into your original post. I think I get what you're saying now. We apply the concept of intelligence to other species, so I don't see w

I may have read too much into your original post. I think I get what you're saying now. We apply the concept of intelligence to other species, so I don't see why we couldn't apply it to machines. If people want to redefine intelligence so that humans stay on top, then they are wrong to do so. There is undeniably an objective component to it, even if there are many cultural factors at play as well. If you don't like the word "intelligence", replace it with "competence", "productivity", "performance", etc. and the same argument will apply. You raised two other issues: the possibility of AGI and the utility of AGI. I think we have good reasons to believe that it's possible. Three possible future scenarios: (1) we get to the point that we can simulate brains to a high degree of accuracy in software, (2) we get to the point that we can build artificial brains out of neurons made of silicon, (3) we get to the point that synthetic biology is advanced enough that we can engineer new kinds of intelligent organisms. These might be science fiction by today's standards, but they show that there is no issue with conceivability. As an aside, the human brain runs on relatively low power consumption and operations per second, so computational power isn't a bottleneck. We have enough compute, we just don't have the right algorithms yet. As for the utility of AGI, I strongly disagree that there is no market for it. By definition, an AGI can do anything that a human can do. There is already a job market for humans. As soon as AGI can compete with humans in domains like management, engineering, scientific research, education, etc. I don't see why there won't be a huge economic incentive to adopt it.

runarberg 4y ago
> As an aside, the human brain runs on relatively low power consumption and operations per second, so computational power isn't a bottleneck. You hit the nail on the head here (pun intended). Brains (and other adoptive biochemical processes which reinforce behavior) are way more ingenious then to be described as a simple computer. It is not just neurons firing in patterns with synapses which can reinforce certain pathways. No, there is a whole biome in our bodies, from our guts, our muscles, through hormonal systems and yes, nervous system. Our behavior is also influenced by bacteria and other microorganisms that doesn’t even share our DNA (but sometimes actually interacts with our DNA). This complex machinery has evolved over millions of years, and I don’t think there is any way for us to simulate it. Even if we look outwards, our behavior is just as much influenced by each other as it is by our brains. So for a successful simulation you’d need to “raise” your machine in a similar manner, allowing interactions with a whole community (or more) that treats it as equal. Our brains are merely a tool which encodes this interaction as learned behavior. Just building a brain will miss all of that and give us a lousy model. In statistics we learn that: “No models are correct, but some models are useful”. I’ve always taken this to mean that there is not always utility in a 100% accurate model. I think this applies for AGI. If we create a machine that can do everything that a human can, and better, what can we use it for? You claim increased competence, productivity, and performance, but we already have machines that do that. And we humans have found a way to work pretty well with those. We even have fully automatic vehicles that transport millions of people every day (e.g. in Vancouver B.C. and Copenhagen). It doesn’t need to be better then humans in everything, just accelerating and decelerating in the right places, it doesn’t need to know the airspeed velocity of an unladen swallow, it will only need to know if something is blocking the tracks. Traditional statistical inference will make these systems better and cheaper, and they will benefit humanity, there is no need for them to have generalized knowledge beyond their immediate utility, so they will never be given one.
- fasterik 4y ago
  I agree with you in the sense that I think many problems don't require general intelligence once you have a solution. However, to come to those solutions it took decades or centuries of intelligent humans working on those problems. The potential benefit of AGI isn't in automating the problems we already know how to solve (although it might help refine our solutions). It's in accelerating progress in domains where there are unsolved problems. Sometimes we get hung up on comparing AI to humans. I wouldn't want an AI that does math and physics in the same way that humans do. Our brains aren't very good at those things. I'm more interested in the potential for AI to find new, more effective ways of working in these areas.

runarberg 4y ago

> As an aside, the human brain runs on relatively low power consumption and operations per second, so computational power isn't a bottleneck. You hit the nail on the head here (pun intended). Brains (and other adoptive biochemical processes which reinforce behavior) are way more ingenious then to be described as a simple computer. It is not just neurons firing in patterns with synapses which can reinforce certain pathways. No, there is a whole biome in our bodies, from our guts, our muscles, through hormonal systems and yes, nervous system. Our behavior is also influenced by bacteria and other microorganisms that doesn’t even share our DNA (but sometimes actually interacts with our DNA). This complex machinery has evolved over millions of years, and I don’t think there is any way for us to simulate it. Even if we look outwards, our behavior is just as much influenced by each other as it is by our brains. So for a successful simulation you’d need to “raise” your machine in a similar manner, allowing interactions with a whole community (or more) that treats it as equal. Our brains are merely a tool which encodes this interaction as learned behavior. Just building a brain will miss all of that and give us a lousy model. In statistics we learn that: “No models are correct, but some models are useful”. I’ve always taken this to mean that there is not always utility in a 100% accurate model. I think this applies for AGI. If we create a machine that can do everything that a human can, and better, what can we use it for? You claim increased competence, productivity, and performance, but we already have machines that do that. And we humans have found a way to work pretty well with those. We even have fully automatic vehicles that transport millions of people every day (e.g. in Vancouver B.C. and Copenhagen). It doesn’t need to be better then humans in everything, just accelerating and decelerating in the right places, it doesn’t need to know the airspeed velocity of an unladen swallow, it will only need to know if something is blocking the tracks. Traditional statistical inference will make these systems better and cheaper, and they will benefit humanity, there is no need for them to have generalized knowledge beyond their immediate utility, so they will never be given one.

fasterik 4y ago
I agree with you in the sense that I think many problems don't require general intelligence once you have a solution. However, to come to those solutions it took decades or centuries of intelligent humans working on those problems. The potential benefit of AGI isn't in automating the problems we already know how to solve (although it might help refine our solutions). It's in accelerating progress in domains where there are unsolved problems. Sometimes we get hung up on comparing AI to humans. I wouldn't want an AI that does math and physics in the same way that humans do. Our brains aren't very good at those things. I'm more interested in the potential for AI to find new, more effective ways of working in these areas.