If anyone knows of a steelman version of the "AGI is not possible" argument, I would be curious to read it. I also have trouble understanding what goes into that point of view.
If you genuinely want the strongest statement of it, read The Emperor's New Mind followed by Shadows of the Mind, both by Roger Penrose.
These books often get shallowly dismissed in terms that imply he made some elementary error in his reasoning, but that's not the case. The dispute is more about the assumptions on which his argument rests, which go beyond mathematical axioms and include statements about the nature of human perception of mathematical truth. That makes it a philosophical debate more than a mathematical one.
Personally, I strongly agree with the non-mathematical assumptions he makes, and am therefore persuaded by his argument. It leads to a very different way of thinking about many aspects of maths, physics and computing than the one I acquired by default from my schooling. It's a perspective that I've become increasingly convinced by over the 30+
years since I first read his books, and one that I think acquires greater urgency as computing becomes an ever larger part of our lives.
2. Humans can create rules outside the system of rules in which they follow
Is number 2 an accurate portrayal? It seems rather suspicious. It seems more likely that we just havent been able to fully express the rules under which humans operate.
To be honest, the core of Penrose’s idea is pretty stupid. That we can understand mathematics despite incompleteness theorem being a thing, therefore our brains use quantum effects allowing us to understand it. Instead of just saying, you know, we use a heuristic instead and just guess that it’s true. I’m pretty sure a classical system can do that.
The whole category of ideas of "Magic Fairy Dust is required for intelligence, and thus, a computer can never be intelligent" is extremely unsound. It should, by now, just get thrown out into the garbage bin, where it rightfully belongs.
My layman thought about that is that, with consciousness, the medium IS the consciousness -- the actual intelligence is in the tangible material of the "circuitry" of the brain. What we call consciousness is an emergent property of an unbelievably complex organ (that we will probably never fully understand or be able to precisely model). Any models that attempt to replicate those phenomena will be of lower fidelity and/or breadth than "true intelligence" (though intelligence is quite variable, of course)... But you get what I mean, right? Our software/hardware models will always be orders of magnitude less precise or exhaustive than what already happens organically in the brain of an intelligent life form. I don't think AGI is strictly impossible, but it will always be a subset or abstraction of "real"/natural intelligence.
I think it's also the case that you can't replicate something actually happening, by describing it.
Baseball stats aren't a baseball game. Baseball stats so detailed that they describe the position of every subatomic particle to the Planck scale during every instant of the game to arbitrarily complete resolution still aren't a baseball game. They're, like, a whole bunch of graphite smeared on a whole bunch of paper or whatever. A computer reading that recording and rendering it on a screen... still isn't a baseball game, at all, not even a little. Rendering it on a holodeck? Nope, 0% closer to actually being the thing, though it's representing it in ways we might find more useful or appealing.
We might find a way to create a conscious computer! Or at least an intelligent one! But I just don't see it in LLMs. We've made a very fancy baseball-stats presenter. That's not nothing, but it's not intelligence, and certainly not consciousness. It's not doing those things, at all.
I think you're tossing around words like "always" or "never" too lightly, with no justification behind them. Why do you think that no matter how much effort is spent, fully understanding the human brain will always be impossible? Always is a really long time. As long as we keep doing research to increasingly precisely model the universe around us, I don't see what would stop this from happening, even if it takes many centuries or millennia. Most people who argue this justify their point by asserting that there is some unprovable quality of the human brain which can't be modeled at all and can only be created in one way - which both lacks substance and seems arbitrary, since I don't think that this relationship provably exists for anything else that we do know about. It seems like a way to justify that humans and only humans are special.
This is how I (also as a layman) look at it as well.
AI right now is limited to trained neural networks, and while they function sort of like a brain, there is no neurogenesis. The trained neural network cannot grow, cannot expand on it's own, and is restrained by the silicon it is running on.
I believe that true AGI will require hardware and models that are able to learn, grow and evolve organically. The next step required for that in my opinion is biocomputing.
The only thing I can come up with is that compressing several hundred million years of natural selection of animal nervous systems into another form, but optimised by gradient descent instead, just takes a lot of time.
Not that we can’t get there by artificial means, but that correctly simulating the environment interactions, the sequence of progression, getting the all the details right, might take hundreds to thousands of years of compute, rather than on the order of a few months.
And it might be that you can get functionally close, but hit a dead end, and maybe hit several dead ends along the way, all of which are close but no cigar. Perhaps LLMs are one such dead end.
I don't disagree, but I think the evolution argument is a red herring. We didn't have to re-engineer horses from the ground up along evolutionary lines to get to much faster and more capable cars.
> correctly simulating the environment interactions, the sequence of progression, getting the all the details right, might take hundreds to thousands of years of compute
Who says we have to do that? Just because something was originally produced by natural process X, that doesn't mean that exhaustively retracing our way through process X is the only way to get there.
The overwhelming majority of animal species never developed (what we would consider) language processing capabilities. So agi doesn't seem like something that evolution is particularly good at producing; more an emergent trait, eventually appearing in things designed simply to not die for long enough to reproduce...
I suppose intelligence can be partitioned as less than, equal to, or greater than human. Given the initial theory depends on natural evidence, one could argue there's no proof that "greater than human" intelligence is possible - depending on your meaning of AGI.
But then intelligence too is a dubious term. An average mind with infinite time and resources might have eventually discovered general relativity.
The steelman would be that knowledge is possible outside the domain of Science. So the opposing argument to evolution as the mechanism for us (the "general intelligence" of AGI) would be that the pathway from conception to you is not strictly material/natural.
Of course, that's not going to be accepted as "Science", but I hope you can at least see that point of view.
the basic idea being that either the human mind is NOT a computation at all (and it's instead spooky unexplainable magic of the universe) and thus can't be replicated by a machine OR it's an inconsistent machine with contradictory logic. and this is a deduction based on godel's incompleteness theorems.
but most people that believe AGI is possible would say the human mind is the latter. technically we don't have enough information today to know either way but we know the human mind (including memories) is fallible so while we don't have enough information to prove the mind is an incomplete system, we have enough to believe it is. but that's also kind of a paradox because that "belief" in unproven information is a cornerstone of consciousness.
The real point isn’t AGI, it’s that the speed of knowledge is empiricism, not intelligence.
An infinitely intelligent creature still has to create a standard model from scratch. We’re leaning too hard on the deductive conception of the world, when reality is, it took hundreds of thousands of years for humans as intelligent as we are to split the atom.
I think the best argument against us ever finding AGI is that the search space is too big and the dead ends are too many. It's like wandering through a monstrously huge maze with hundreds of very convincingly fake exits that lead to pit traps. The first "AGI" may just be a very convincing Chinese room that kills all of humanity before we can ever discover an actual AGI.
The necessary conditions for "Kill all Humanity" may be the much more common result than "Create a novel thinking being." To the point where it is statistically improbable for the human race to reach AGI. Especially since a lot of AI research is specifically for autonomous weapons research.
Is there a plausible situation where a humanity-killing superintelligence isn't vulnerable to nuclear weapons?
If a genuine AGI-driven human extinction scenario arises, what's to stop the world's nuclear powers from using high-altitude detonations to produce a series of silicon-destroying electromagnetic pulses around the globe? It would be absolutely awful for humanity don't get me wrong, but it'd be a damn sight better than extinction.
If you have a wide enough definition of AGI having a baby is making “AGI.” It’s a human made, generally intelligent thing. What people mean by the “A” though is we have some kind of inorganic machine realize the traits of “intelligence” in the medium of a computer.
The first leg of the argument would be that we aren’t really sure what general intelligence is or if it’s a natural category. It’s sort of like “betterness.” There’s no general thing called “betterness” that just makes you better at everything. To get better at different tasks usually requires different things.
I would be willing to concede to the AGI crowd that there could be something behind g that we could call intelligence. There’s a deeper problem though that the first one hints at.
For AGI to be possible, whatever trait or traits make up “intelligence” need to have multiple realizablity. They need to be at least realizable in both the medium of a human being and at least some machine architectures. In programmer terms, the traits that make up intelligence could be tightly coupled to the hardware implementation. There are good reasons to think this is likely.
Programmers and engineers like myself love modular systems that are loosely coupled and cleanly abstracted. Biology doesn’t work this way — things at the molecular level can have very specific effects on the macro scale and vice versa. There’s little in the way of clean separation of layers. Who is to say that some of the specific ways we work at a cellular level aren’t critical to being generally intelligent? That’s an “ugly” idea but lots of things in nature are ugly. Is it a coincidence too that humans are well adapted to getting around physically, can live in many different environments, etc.? There’s also stuff from the higher level — does living physically and socially in a community of other creatures play a key role in our intelligence? Given how human beings who grow up absent those factors are developmentally disabled in many ways it would seem so. It could be there’s a combination of factors here, where very specific micro and macro aspects of being a biological human turn out to contribute and you need the perfect storm of these aspects to get a generally intelligent creature. Some of these aspects could be realizable and computers, but others might not be, at least in a computationally tractable way.
It’s certainly ugly and goes against how we like things to work for intelligence to require a big jumbly mess of stuff, but nature is messy. Given the only known case of generally intelligent life is humans, the jury is still out that you can do it any other way.
Another commenter mentioned horses and cars. We could build cars that are faster than horses, but speed is something that is shared by all physical bodies and is therefore eminently multiply realizable. But even here, there are advantages to horses that cars don’t have, and which are tied up with very specific aspects of being a horse. Horses generally can go over a wider range of terrain than cars. This is intrinsically tied to them having long legs and four hooves instead of rubber wheels. They’re only able to have such long legs because of their hooves too because the hooves are required to help them pump blood when they run, and that means that in order for them to pump their blood successfully they NEED to run fast on a regular basis. there’s a deep web of influence both on a part-to-part, and the whole macro-level behaviors of horses. Having this more versatile design also has intrinsic engineering trade-offs. A horse isn’t ever going to be as fast as a gas powered four-wheeled vehicle on flat ground but you definitely can’t build a car that can do everything a horse can do with none of the drawbacks. Even if you built a vehicle that did everything a horse can do, but was faster, I would bet you it would be way more expensive and consume much more energy than a horse. There’s no such thing as a free lunch in engineering. You could also build a perfect replica of a horse at a molecular level and claim you have your artificial general horse.
Similarly, human beings are good at a lot of different things besides just being smart. But maybe you need to be good at seeing, walking, climbing, acquiring sustenance, etc. In order to be generally intelligent in a way that’s actually useful. I also suspect our sense of the beautiful, the artistic is deeply linked with our wider ability to be intelligent.
Finally it’s an open philosophical question whether human consciousness is explainable in material terms at all. If you are a naturalist, you are methodologically committed to this being the case — but that’s not the same thing as having definitive evidence that it is so. That’s an open research project.
In short, by definition, computers are symbol manipulating devices. However complex the rules of symbol manipulation, it is still a symbol manipulating device, and therefore neither intelligent nor sentient. So AGI on computers is not possible.
This is not an argument at all, you just restate your whole conclusion as an assumption ("a symbol manipulating device is incapable of cognition").
It's not even a reasonable assumption (to me), because I'd assume an exact simulation of a human brain to have the exact same cognitive capabilities (which is inevitable, really, unless you believe in magic).
And machines are well capable of simulating physics.
I'm not advocating for that approach because it is obviously extremely inefficient; we did not achieve flight by replicating flapping wings either, after all.
Computer can simulate human brain on subatomic level (in theory). Do you agree this would be "sentient and intelligent" and not just symbol manipulating?
omnicognate|4 months ago
These books often get shallowly dismissed in terms that imply he made some elementary error in his reasoning, but that's not the case. The dispute is more about the assumptions on which his argument rests, which go beyond mathematical axioms and include statements about the nature of human perception of mathematical truth. That makes it a philosophical debate more than a mathematical one.
Personally, I strongly agree with the non-mathematical assumptions he makes, and am therefore persuaded by his argument. It leads to a very different way of thinking about many aspects of maths, physics and computing than the one I acquired by default from my schooling. It's a perspective that I've become increasingly convinced by over the 30+ years since I first read his books, and one that I think acquires greater urgency as computing becomes an ever larger part of our lives.
nonethewiser|4 months ago
1. Any formal mathematical system (including computers) have true statements that cannot be proven within that system.
2. Humans can see the truth of some such unprovable statements.
Which is basically Gödel's Incompleteness Theorem. https://en.wikipedia.org/wiki/G%C3%B6del%27s_incompleteness_...
Maybe a more ELI5
1. Computers follow set rules
2. Humans can create rules outside the system of rules in which they follow
Is number 2 an accurate portrayal? It seems rather suspicious. It seems more likely that we just havent been able to fully express the rules under which humans operate.
myrmidon|4 months ago
If you are interested in the opposite point of view, I can really recommend "Vehicles: Experiments in Synthetic Psychology" by V. Braitenberg.
Basically builds up to "consciousness as emergent property" in small steps.
Chance-Device|4 months ago
ACCount37|4 months ago
The whole category of ideas of "Magic Fairy Dust is required for intelligence, and thus, a computer can never be intelligent" is extremely unsound. It should, by now, just get thrown out into the garbage bin, where it rightfully belongs.
nemo1618|4 months ago
amatecha|4 months ago
walkabout|4 months ago
Baseball stats aren't a baseball game. Baseball stats so detailed that they describe the position of every subatomic particle to the Planck scale during every instant of the game to arbitrarily complete resolution still aren't a baseball game. They're, like, a whole bunch of graphite smeared on a whole bunch of paper or whatever. A computer reading that recording and rendering it on a screen... still isn't a baseball game, at all, not even a little. Rendering it on a holodeck? Nope, 0% closer to actually being the thing, though it's representing it in ways we might find more useful or appealing.
We might find a way to create a conscious computer! Or at least an intelligent one! But I just don't see it in LLMs. We've made a very fancy baseball-stats presenter. That's not nothing, but it's not intelligence, and certainly not consciousness. It's not doing those things, at all.
tavavex|4 months ago
kraquepype|4 months ago
AI right now is limited to trained neural networks, and while they function sort of like a brain, there is no neurogenesis. The trained neural network cannot grow, cannot expand on it's own, and is restrained by the silicon it is running on.
I believe that true AGI will require hardware and models that are able to learn, grow and evolve organically. The next step required for that in my opinion is biocomputing.
Chance-Device|4 months ago
Not that we can’t get there by artificial means, but that correctly simulating the environment interactions, the sequence of progression, getting the all the details right, might take hundreds to thousands of years of compute, rather than on the order of a few months.
And it might be that you can get functionally close, but hit a dead end, and maybe hit several dead ends along the way, all of which are close but no cigar. Perhaps LLMs are one such dead end.
danielbln|4 months ago
squidbeak|4 months ago
alexwebb2|4 months ago
Who says we have to do that? Just because something was originally produced by natural process X, that doesn't mean that exhaustively retracing our way through process X is the only way to get there.
Lab grown diamonds are a thing.
sdenton4|4 months ago
disambiguation|4 months ago
But then intelligence too is a dubious term. An average mind with infinite time and resources might have eventually discovered general relativity.
throw7|4 months ago
Of course, that's not going to be accepted as "Science", but I hope you can at least see that point of view.
itsnowandnever|4 months ago
the basic idea being that either the human mind is NOT a computation at all (and it's instead spooky unexplainable magic of the universe) and thus can't be replicated by a machine OR it's an inconsistent machine with contradictory logic. and this is a deduction based on godel's incompleteness theorems.
but most people that believe AGI is possible would say the human mind is the latter. technically we don't have enough information today to know either way but we know the human mind (including memories) is fallible so while we don't have enough information to prove the mind is an incomplete system, we have enough to believe it is. but that's also kind of a paradox because that "belief" in unproven information is a cornerstone of consciousness.
scoofy|4 months ago
An infinitely intelligent creature still has to create a standard model from scratch. We’re leaning too hard on the deductive conception of the world, when reality is, it took hundreds of thousands of years for humans as intelligent as we are to split the atom.
foxyv|4 months ago
The necessary conditions for "Kill all Humanity" may be the much more common result than "Create a novel thinking being." To the point where it is statistically improbable for the human race to reach AGI. Especially since a lot of AI research is specifically for autonomous weapons research.
BoxOfRain|4 months ago
If a genuine AGI-driven human extinction scenario arises, what's to stop the world's nuclear powers from using high-altitude detonations to produce a series of silicon-destroying electromagnetic pulses around the globe? It would be absolutely awful for humanity don't get me wrong, but it'd be a damn sight better than extinction.
jact|4 months ago
The first leg of the argument would be that we aren’t really sure what general intelligence is or if it’s a natural category. It’s sort of like “betterness.” There’s no general thing called “betterness” that just makes you better at everything. To get better at different tasks usually requires different things.
I would be willing to concede to the AGI crowd that there could be something behind g that we could call intelligence. There’s a deeper problem though that the first one hints at.
For AGI to be possible, whatever trait or traits make up “intelligence” need to have multiple realizablity. They need to be at least realizable in both the medium of a human being and at least some machine architectures. In programmer terms, the traits that make up intelligence could be tightly coupled to the hardware implementation. There are good reasons to think this is likely.
Programmers and engineers like myself love modular systems that are loosely coupled and cleanly abstracted. Biology doesn’t work this way — things at the molecular level can have very specific effects on the macro scale and vice versa. There’s little in the way of clean separation of layers. Who is to say that some of the specific ways we work at a cellular level aren’t critical to being generally intelligent? That’s an “ugly” idea but lots of things in nature are ugly. Is it a coincidence too that humans are well adapted to getting around physically, can live in many different environments, etc.? There’s also stuff from the higher level — does living physically and socially in a community of other creatures play a key role in our intelligence? Given how human beings who grow up absent those factors are developmentally disabled in many ways it would seem so. It could be there’s a combination of factors here, where very specific micro and macro aspects of being a biological human turn out to contribute and you need the perfect storm of these aspects to get a generally intelligent creature. Some of these aspects could be realizable and computers, but others might not be, at least in a computationally tractable way.
It’s certainly ugly and goes against how we like things to work for intelligence to require a big jumbly mess of stuff, but nature is messy. Given the only known case of generally intelligent life is humans, the jury is still out that you can do it any other way.
Another commenter mentioned horses and cars. We could build cars that are faster than horses, but speed is something that is shared by all physical bodies and is therefore eminently multiply realizable. But even here, there are advantages to horses that cars don’t have, and which are tied up with very specific aspects of being a horse. Horses generally can go over a wider range of terrain than cars. This is intrinsically tied to them having long legs and four hooves instead of rubber wheels. They’re only able to have such long legs because of their hooves too because the hooves are required to help them pump blood when they run, and that means that in order for them to pump their blood successfully they NEED to run fast on a regular basis. there’s a deep web of influence both on a part-to-part, and the whole macro-level behaviors of horses. Having this more versatile design also has intrinsic engineering trade-offs. A horse isn’t ever going to be as fast as a gas powered four-wheeled vehicle on flat ground but you definitely can’t build a car that can do everything a horse can do with none of the drawbacks. Even if you built a vehicle that did everything a horse can do, but was faster, I would bet you it would be way more expensive and consume much more energy than a horse. There’s no such thing as a free lunch in engineering. You could also build a perfect replica of a horse at a molecular level and claim you have your artificial general horse.
Similarly, human beings are good at a lot of different things besides just being smart. But maybe you need to be good at seeing, walking, climbing, acquiring sustenance, etc. In order to be generally intelligent in a way that’s actually useful. I also suspect our sense of the beautiful, the artistic is deeply linked with our wider ability to be intelligent.
Finally it’s an open philosophical question whether human consciousness is explainable in material terms at all. If you are a naturalist, you are methodologically committed to this being the case — but that’s not the same thing as having definitive evidence that it is so. That’s an open research project.
slow_typist|4 months ago
myrmidon|4 months ago
It's not even a reasonable assumption (to me), because I'd assume an exact simulation of a human brain to have the exact same cognitive capabilities (which is inevitable, really, unless you believe in magic).
And machines are well capable of simulating physics.
I'm not advocating for that approach because it is obviously extremely inefficient; we did not achieve flight by replicating flapping wings either, after all.
progbits|4 months ago
If yes, everything else is just optimization.