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Q&A: Douglas Hofstadter on why AI is far from intelligent

105 points by pilingual 9y ago

kenjackson 9y ago
What frightens me is the scenario of human thought being overwhelmed and left in the dust. Not being aided or abetted by computers, but being completely overwhelmed, and we are to computers as cockroaches or fleas are to us. That would be scary. This implies to me that his definition of intelligence is really centered on what we as humans do. And that is interesting, but less interesting than a more general notion of intelligence.
- sorokod 9y ago
  Not necessarily. It just means that ML based approach may be better than whatever it is we humans do in enough tasks to make the humans irrelevant. Think calligraphy Vs. the printing press.
  - astrodust 9y ago
    I'm sure some people thought the printing press was the devil incarnate as it took the human element out of books. Prior to that every letter, every page, was produced with some measure of human effort. Holding that work, reading those letters, was something special. Now there's no direct physical connection between what we write and the book someone holds, yet we don't run around screaming that automated printing has destroyed writing. With intelligence this is likely to be the same thing: AI can amplify regular intelligence just as the printing press can amplify the ability of one writer to reach more people.
    - pixl97 9y ago
      >yet we don't run around screaming that automated printing has destroyed writing. I disagree in part. There have been many complaints voiced about bots in modern digital book distribution producing tons of crap and flooding markets like amazon.com with junk. It doesn't take very many processes like this to produce a corpus of information larger than has been created by mankind. So in some sense of the word, bots have 'destroyed' writing by volume. Now that said, most of it will never be seen in a place where it causes interruption to shoppers or readers, as it will get filtered out by the distributors. That said, this makes a mess of unfiltered distributed systems of digital books.
      - astrodust 9y ago
        Where bots can flood the market with junk, bots can flag and remove junk books, or at least push them down in terms of visibility. The problem is Amazon doesn't seem the least bit motivated to even try here.
  - runeks 9y ago
    > It just means that ML based approach may be better than whatever it is we humans do in enough tasks to make the humans irrelevant. Given that more and more people are employed in ML-related jobs, what makes you think advances in ML will render humans irrelevant? Seems to me like the opposite is happening right now.
    - sorokod 9y ago
      They are unlikely to be the same people and it is likely that less people will be required.
KiwiCoder 9y ago
Suppose a simulated intelligence was indistinguishable from real intelligence. In what sense would it matter that it was a simulation and not real?
- robotresearcher 9y ago
  That’s the standard zombie argument. It’s weakness is that the premise is not reasonable. If the premise is true, the argument is compelling. But there is no strong evidence that the premise is true or possible. Please note that I haven’t taken a stance on this here myself, so there’s no need to argue with me about the truth or falsity of the premise. I’m just explaining the problem with the zombie argument.
- trumpownsyou420 9y ago
  it doesn't, but lots of people get hung up on that kind of stuff.
- astrodust 9y ago
  We're just a simulation of intelligence that's done with clunky, inelegant biological materials. The only thing that separates humans from slugs is scale and complexity of neural interconnections, all the basic parts are present in a slug. Intelligence itself is an emergent phenomenon, so who's to say what's "simulated" and what's "real"? If it behaves in an intelligent manner, which can be tested and probed exhaustively, then it is intelligent.
- peter303 9y ago
  How do you know you havevsome intelligence? Youcan only explain a small part how it works. Ditto only replicate a few intelligent activites.
- firasd 9y ago
  "The self is a kind of fiction, for hosts and humans alike. It's a story we tell ourselves... there is no threshold that makes us greater than the sum of our parts, no inflection point at which we become fully alive." -- Dr. Ford, Westworld (video contains spoilers) https://www.youtube.com/watch?v=S94ETUiMZwQ https://www.youtube.com/watch?v=S94ETUiMZwQ
unholiness 9y ago
The further we get into the future, the more I think, what if our data-crunching approach to AI is simply the best thing there is? Hofstadter said in GEB (in 1979) that the only program that could be capable of beating the best humans at chess would need to be a general and human intelligence... human enough to decline your suggestion to play chess, and suggest you talk about poetry instead. It seems that people today are still engaging in the same sort of fallacy. I keep hearing that deep learning is too hyper-specialized, that it's a tool and not an intelligence, that we're still waiting for a revolution of general intelligence, where intelligences will have sophisticated logic and make their decisions without billions of data points, just like humans do. My counter-hypothesis is this: Computers, compared to humans, will always be more data-hungry (i.e. worse at making general decisions without huge amounts of data) and more data-capable (i.e. better at making decisions with it). And this isn't really a bad thing. We will still see revolutions allowing more and more general problems to be solved, revolutions allowing more and more general data to be considered, and revolutions giving more and more usable interfaces for inputing data and specifying problems. We'll still see data-driven intelligent assistants and data-driven board members making critical decisions like in everyone's utopian dreams/dystopian nightmares. But these foretold "general" intelligences, who don't need excessive data, the intelligences who beat the Turing test, the intelligences who "want" things and "feel" things, who attempt to solve the problem of replicating humans... those come unimaginably far in the future. And when they do arrive, they won't really solve any problems that the data-crunchers haven't already solved better.
- emmab 9y ago
  > capable of making decisions without billions of data points, just like humans do. Doesn't this ignore transfer learning? Humans have orders of magnitude more than billions of data points over their lifetimes.
  - komaromy 9y ago
    Additionally, we have absurd amounts of information baked into our genes that give us big head starts on network architectures, motion, vision, etc.
pjungwir 9y ago
I am curious if we will someday build AI systems that are stratified with layers alternating between "statistical" like neural networks and "symbolic" like the older AI approaches. For example once your image recognition NN is tagging things, you could feed those tags into a more symbolic reasoning system. In theory Deep Learning should make this unnecessary (I guess?), but in practice these layers would be very useful. First they would make the system more interpretable. When your AI is a black box you don't learn anything. It would be nicer if we could gain heuristics or principles that we didn't know before, and apply them ourselves. Second with layers we wouldn't have to trust the AI so blindly. We could see if its thinking makes sense. In particular many AI applications can create feedback loops where it can perform well at first, but we'd like to keep monitoring it to ensure it stays that way. If neural networks resemble our unconscious then symbolic systems resemble our reason---like "Thinking Fast and Slow". Some people say we must be able to do "better" than NNs since babies don't need to see millions of dogs to recognize them. But the pixel-inputs of a NN do seem a lot like the rods & cones inputs of our vision, and one huge advantage of human perception is seeing in the flow of time. Our observations aren't millions of discrete snapshots, but millions of connected moments. I wonder how image recognition training would improve if we trained by showing short videos instead of still images. It seems that would make it a lot easier to recognize boundaries and possible variations. In humans, our unconscious is not something we can easily "see" and reflect on and correct, but our reason is reflective. We can articulate principles and opinions and judgments. We can re-use them and continually challenge them, question them, modify them, even reject them. There is a cynical idea that reason is nothing but post facto rationalization, and maybe it often is, but we needn't live that way. We can live an examined life if we choose. But I can't imagine a machine ever achieving that reflexivity without a symbolic system. And isn't that awareness close to what we mean by "consciousness"? Somewhere, I think in Jacques Maritain, I came across the definition of consciousness as simply awareness of the self, in particular that the self exists. Being able to recognize ideas as "mine" and reflect on them also seems like part of what consciousness is all about.
- pixl97 9y ago
  >Some people say we must be able to do "better" than NNs since babies don't need to see millions of dogs to recognize them. I always hate that example. A dog is not a thing. A dog is a collection of things. By the time a baby sees a collection of things that is a dog, it has already had a huge amount of experience in identifying individual parts, such as faces and eyes. Of course, I wish we knew how to program AI systems that way. > I came across the definition of consciousness as simply awareness of the self, in particular that the self exists. If you are intelligent you can cause enough complex changes to the environment around you, this means you can get caught in 'advanced' feedback loops. If you don't want to waste massive amounts of energy, or even die, it is beneficial to be able to separate "this was caused by me and my actions" from "this was someone/thing else that did this".
sgt101 9y ago
A two minute old gazelle can out perform and current Ai in terms of navigating a real world. Data processing isn't the whole thing.
- yathern 9y ago
  A two minute old gazelle is born with a lot of pretrained instincts. Instincts built from a genetic optimization algorithm that's been going on for millions of years. Spacial reasoning and "run from predators" is not something it needs to be taught. The data processing is already baked in.
  - goatlover 9y ago
    The point is that being "baked in" is something machines lack which biological intelligences possess. Animal brains don't learn those "baked in" abilities. We may need to "bake in" similar abilities into the AIs, since we recreating evolution is computationally prohibitive.
    - pixl97 9y ago
      >since we recreating evolution is computationally prohibitive. You don't see what you did there. The only way to 'bake in' these things is to create them via evolution in the first place. Also, these instincts are not 'baked' they continue to evolve with each generation.
    - runeks 9y ago
      > The point is that being "baked in" is something machines lack which biological intelligences possess. I’d say it’s the exact opposite: A freshly born CPU is as a capable as it will ever be. The problem is that it never learns anything new, as opposed to biological organisms which continuously adapt to their environment.
      - xapata 9y ago
        Once the CPU runs a chip factory, it'll be able to adapt in a sense.
dgreensp 9y ago
I think it’s really important to distinguish 1. pure problem-solving (chess, go) from 2. competency of behavior in the world (vision, navigating a maze), from 3. universal cognitive-emotional life (getting frustrated trying to accomplish a goal and trying a different approach; having competing drives that form the basis for goal-setting, like hunger, boredom, and self-preservation), from 4. more arbitrary-seeming, human-like cognitive emotions, like humor and beauty. You can have 1 and 2 without anything directly resembling human intelligence, and 3 with animal-like intelligence, or you could make something completely alien. An appreciation of humor and beauty would be a great way to demonstrate you’ve made something like a virtual “human mind.” There’s no reason computers couldn’t be better at all of these things, including writing better jokes. There’s a funny blog post somewhere about the idea of a computer writing superhuman-level funny jokes; I wish I remembered where!
- GuiA 9y ago
  3 and 4 are pretty hard to beat though, because humans have decades and decades of input and feedback loops with other humans to develop them. Who’s gonna play hide and seek and read bedtime stories every night to the computers?
  - dgreensp 9y ago
    “Embodiment” is most important for 2, and to fool humans into thinking you are a real human (as in the Turing test), able to talk about the human experience and relate to other humans. Animals (including humans) are born with a version of 3 (and 4). Emotions are simple. Thought-level nuance is learned over time, but data learned by one android (or whatever) can be shared. Also, children are able to learn from comparatively few data points, and computers are beginning to do this too (see “one-shot” learning, learning from one occurrence, like the way kids sometimes pick things up). If you make a child android that looks and acts like a child, people will read to it and play with it; there are movies about this! :)
    - dgreensp 9y ago
      It would take a lot for a computer to write a beautiful novel, say. But not to appreciate and create beauty in other ways. And I really think computers could write some excellent jokes along the way to becoming more human. Pretty much anything they learn to do can be used for comedy. Physical movement with “character” gone wrong leads to physical comedy. Common-sense knowledge leads to common-sense comedy (like the joke about the elephant leaving tracks in the butter dish, which kids of a certain age find funny but adults seem to have grown out of).
arikrak 9y ago
This is not at all how computers play chess: > A computer can beat a human at chess not by searching for the satisfaction of making an elegant move, but sifting through millions of previously played games to see which move is more likely to lead to victory.
- deleted 9y ago
  [deleted]
- xapata 9y ago
  Not historically for chess, but it's a reasonable analogy for how AlphaGo plays Go.
- ubernostrum 9y ago
  A lot depends on the era you're talking about, for computer chess. It used to be that forcing a chess computer out of its "book", so that it had to start relying on move-tree searches much earlier in the game when that tree is still monstrous in size, was a good or at least OK tactic. As the computers got better, and as more effort was put into anti-anti-computer tactics, it stopped being useful, but to say that this is "not at all" how computers have played chess is incorrect.
  - yesenadam 9y ago
    And it's also not what they said.
danielam 9y ago
I thought the beginning of the interview showed promise, but toward the end the conversation unmoors from the topic at hand. I really do wonder how many in the field of AI take as philosophically unsophisticated of an idea like intelligent computers seriously and see it as an obvious and uncontroversial possibility. What Hofstadter is dancing around is that intelligence requires semantics and semantics is exactly what computers, by definition, lack. Knowledge is semantic in nature and thus computers cannot, strictly speaking, know anything. They cannot reason because, again, reason requires semantics. Now, we are able to model and then formalize some domains of reality under some aspect well enough such that computers can behave in very useful ways, but no matter how sophisticated such programming gets, it cannot somehow magically cross over into semantics. The notion is patently absurd. So to say that AI is, literally, far from being intelligent is like saying the color red is far from being a strawberry. No amount of red will ever amount to a strawberry. P.S. I was reminded of this post about Sphex wasps and intelligence, with mention of Dennett and Hofstadter: http://edwardfeser.blogspot.com/2013/12/da-ya-think-im-sphexy.html http://edwardfeser.blogspot.com/2013/12/da-ya-think-im-sphex...
- jedharris 9y ago
  Please explain how to tell if some being "has semantics". Suppose we encounter some alien made out of crystal and metal, but arranged in organic looking structures. We work out how to communicate, rather roughly (like Google Translate). They won't talk about their ancestors so we don't know if they were built or evolved. How do we find out if they have semantics?
  - danielam 9y ago
    Computers aren't a black box mystery. We understand how they work. We understand that they are implementations of Turing machines (or similar computational models), and Turing machines are by definition a formalism and thus syntactic in nature. Computers are therefore no more than syntactic machines (I would further claim that computers aren't strictly speaking syntactic machines either, but physical artifacts -- and we can use different physical properties and states toward this end -- that simulate a formalized, syntactical system). Syntax as such is semantically blind, so to speak. Human beings, on the other hand, do "possess" meanings. We have concepts. Pure syntax can never amount to a single concept anymore than purely speaking about climbing Mt. Everest ever itself amounts to actually climbing Mt. Everest. Any semantics we associate with computer programs is entirely an act of interpretation on the human end.
lisper 9y ago
Something often missed when talking about GAI is that we humans are built by our genes in order to facilitate their (not our) reproduction. Genes don't care about anything, not even reproduction (except in the sense that water cares about flowing down hill), but one of the tricks they use to advance their "agenda" is to build brains that do care about things. A lot of what we call "intelligence" is actually a side-effect of caring about things more than it is evidence of thinking. In particular, it's a side-effect of caring about the kinds of things that advance our reproductive fitness. For example: Hofstadter laments that, although computers can now trounce the best humans in chess, they don't look for "elegant moves" or decline to play and have tea instead. Hofstadter cares about these things because chess is more than an abstract mathematical construct. It is, like all sporting events, a social construct, one that distills the essence of competition where the participants care about who wins and who loses. And all of this derives from evolution where genes that build brains that care about winning competitions outperform genes that don't. One of the things holding back computers from being GAIs is that we have not yet figured out how to make them care about anything, and so they cannot possibly understand the visceral difference between winning and losing, or the emotional angst of being up against a deadline or deciding to take a risk. All of these are part and parcel of everything we humans do. The ability to do math is just an interesting and useful side-effect, but it was never the main event. Personally, I think it's a good thing that we don't know how to make computers care about things because once we figure that out they really will become potentially dangerous. Our desires are hard-wired into us by our genes. Once computers have desires of their own, their interests may align with ours, but that's not a given. And if they don't, that could be a really big problem.
- galaxyLogic 9y ago
  True, but it's good to keep in mind that genes don't have an "agenda" either. They just are the way they are because they survived. It's like having a neighbor who just won $100 million in lottery and thinking, vow, what is his secret? How could he do that? I don't think I could ever do that. How did he do it? The fact is he didn't have much to do with it, it was all pure chance.
  - 9y ago
sonink 9y ago
> What frightens me is the scenario of human thought being overwhelmed and left in the dust. Not being aided or abetted by computers, but being completely overwhelmed, and we are to computers as cockroaches or fleas are to us. That would be scary. I suspect our expectation of GAI is unreasonable and we will sooner or later have to reconcile it with a different and less anthropomorphic expression of intelligence and consciousness. It might not be required for AI to be (anthrophomorphically) intelligent or conscious for it to 'take over'. Infact it might be a huge advance over mankind that it is not.

105 points by pilingual 9y ago

What frightens me is the scenario of human thought being overwhelmed and left in the dust. Not being aided or abetted by computers, but being completely overwhelmed, and we are to computers as cockroaches or fleas are to us. That would be scary. This implies to me that his definition of intelligence is really centered on what we as humans do. And that is interesting, but less interesting than a more general notion of intelligence.

sorokod 9y ago
Not necessarily. It just means that ML based approach may be better than whatever it is we humans do in enough tasks to make the humans irrelevant. Think calligraphy Vs. the printing press.
- astrodust 9y ago
  I'm sure some people thought the printing press was the devil incarnate as it took the human element out of books. Prior to that every letter, every page, was produced with some measure of human effort. Holding that work, reading those letters, was something special. Now there's no direct physical connection between what we write and the book someone holds, yet we don't run around screaming that automated printing has destroyed writing. With intelligence this is likely to be the same thing: AI can amplify regular intelligence just as the printing press can amplify the ability of one writer to reach more people.
  - pixl97 9y ago
    >yet we don't run around screaming that automated printing has destroyed writing. I disagree in part. There have been many complaints voiced about bots in modern digital book distribution producing tons of crap and flooding markets like amazon.com with junk. It doesn't take very many processes like this to produce a corpus of information larger than has been created by mankind. So in some sense of the word, bots have 'destroyed' writing by volume. Now that said, most of it will never be seen in a place where it causes interruption to shoppers or readers, as it will get filtered out by the distributors. That said, this makes a mess of unfiltered distributed systems of digital books.
    - astrodust 9y ago
      Where bots can flood the market with junk, bots can flag and remove junk books, or at least push them down in terms of visibility. The problem is Amazon doesn't seem the least bit motivated to even try here.
- runeks 9y ago
  > It just means that ML based approach may be better than whatever it is we humans do in enough tasks to make the humans irrelevant. Given that more and more people are employed in ML-related jobs, what makes you think advances in ML will render humans irrelevant? Seems to me like the opposite is happening right now.
  - sorokod 9y ago
    They are unlikely to be the same people and it is likely that less people will be required.

KiwiCoder 9y ago

Suppose a simulated intelligence was indistinguishable from real intelligence. In what sense would it matter that it was a simulation and not real?

robotresearcher 9y ago
That’s the standard zombie argument. It’s weakness is that the premise is not reasonable. If the premise is true, the argument is compelling. But there is no strong evidence that the premise is true or possible. Please note that I haven’t taken a stance on this here myself, so there’s no need to argue with me about the truth or falsity of the premise. I’m just explaining the problem with the zombie argument.
trumpownsyou420 9y ago
it doesn't, but lots of people get hung up on that kind of stuff.
astrodust 9y ago
We're just a simulation of intelligence that's done with clunky, inelegant biological materials. The only thing that separates humans from slugs is scale and complexity of neural interconnections, all the basic parts are present in a slug. Intelligence itself is an emergent phenomenon, so who's to say what's "simulated" and what's "real"? If it behaves in an intelligent manner, which can be tested and probed exhaustively, then it is intelligent.
peter303 9y ago
How do you know you havevsome intelligence? Youcan only explain a small part how it works. Ditto only replicate a few intelligent activites.
firasd 9y ago
"The self is a kind of fiction, for hosts and humans alike. It's a story we tell ourselves... there is no threshold that makes us greater than the sum of our parts, no inflection point at which we become fully alive." -- Dr. Ford, Westworld (video contains spoilers) https://www.youtube.com/watch?v=S94ETUiMZwQ https://www.youtube.com/watch?v=S94ETUiMZwQ

unholiness 9y ago

The further we get into the future, the more I think, what if our data-crunching approach to AI is simply the best thing there is? Hofstadter said in GEB (in 1979) that the only program that could be capable of beating the best humans at chess would need to be a general and human intelligence... human enough to decline your suggestion to play chess, and suggest you talk about poetry instead. It seems that people today are still engaging in the same sort of fallacy. I keep hearing that deep learning is too hyper-specialized, that it's a tool and not an intelligence, that we're still waiting for a revolution of general intelligence, where intelligences will have sophisticated logic and make their decisions without billions of data points, just like humans do. My counter-hypothesis is this: Computers, compared to humans, will always be more data-hungry (i.e. worse at making general decisions without huge amounts of data) and more data-capable (i.e. better at making decisions with it). And this isn't really a bad thing. We will still see revolutions allowing more and more general problems to be solved, revolutions allowing more and more general data to be considered, and revolutions giving more and more usable interfaces for inputing data and specifying problems. We'll still see data-driven intelligent assistants and data-driven board members making critical decisions like in everyone's utopian dreams/dystopian nightmares. But these foretold "general" intelligences, who don't need excessive data, the intelligences who beat the Turing test, the intelligences who "want" things and "feel" things, who attempt to solve the problem of replicating humans... those come unimaginably far in the future. And when they do arrive, they won't really solve any problems that the data-crunchers haven't already solved better.

emmab 9y ago
> capable of making decisions without billions of data points, just like humans do. Doesn't this ignore transfer learning? Humans have orders of magnitude more than billions of data points over their lifetimes.
- komaromy 9y ago
  Additionally, we have absurd amounts of information baked into our genes that give us big head starts on network architectures, motion, vision, etc.

pjungwir 9y ago

I am curious if we will someday build AI systems that are stratified with layers alternating between "statistical" like neural networks and "symbolic" like the older AI approaches. For example once your image recognition NN is tagging things, you could feed those tags into a more symbolic reasoning system. In theory Deep Learning should make this unnecessary (I guess?), but in practice these layers would be very useful. First they would make the system more interpretable. When your AI is a black box you don't learn anything. It would be nicer if we could gain heuristics or principles that we didn't know before, and apply them ourselves. Second with layers we wouldn't have to trust the AI so blindly. We could see if its thinking makes sense. In particular many AI applications can create feedback loops where it can perform well at first, but we'd like to keep monitoring it to ensure it stays that way. If neural networks resemble our unconscious then symbolic systems resemble our reason---like "Thinking Fast and Slow". Some people say we must be able to do "better" than NNs since babies don't need to see millions of dogs to recognize them. But the pixel-inputs of a NN do seem a lot like the rods & cones inputs of our vision, and one huge advantage of human perception is seeing in the flow of time. Our observations aren't millions of discrete snapshots, but millions of connected moments. I wonder how image recognition training would improve if we trained by showing short videos instead of still images. It seems that would make it a lot easier to recognize boundaries and possible variations. In humans, our unconscious is not something we can easily "see" and reflect on and correct, but our reason is reflective. We can articulate principles and opinions and judgments. We can re-use them and continually challenge them, question them, modify them, even reject them. There is a cynical idea that reason is nothing but post facto rationalization, and maybe it often is, but we needn't live that way. We can live an examined life if we choose. But I can't imagine a machine ever achieving that reflexivity without a symbolic system. And isn't that awareness close to what we mean by "consciousness"? Somewhere, I think in Jacques Maritain, I came across the definition of consciousness as simply awareness of the self, in particular that the self exists. Being able to recognize ideas as "mine" and reflect on them also seems like part of what consciousness is all about.

pixl97 9y ago
>Some people say we must be able to do "better" than NNs since babies don't need to see millions of dogs to recognize them. I always hate that example. A dog is not a thing. A dog is a collection of things. By the time a baby sees a collection of things that is a dog, it has already had a huge amount of experience in identifying individual parts, such as faces and eyes. Of course, I wish we knew how to program AI systems that way. > I came across the definition of consciousness as simply awareness of the self, in particular that the self exists. If you are intelligent you can cause enough complex changes to the environment around you, this means you can get caught in 'advanced' feedback loops. If you don't want to waste massive amounts of energy, or even die, it is beneficial to be able to separate "this was caused by me and my actions" from "this was someone/thing else that did this".

sgt101 9y ago

A two minute old gazelle can out perform and current Ai in terms of navigating a real world. Data processing isn't the whole thing.

yathern 9y ago
A two minute old gazelle is born with a lot of pretrained instincts. Instincts built from a genetic optimization algorithm that's been going on for millions of years. Spacial reasoning and "run from predators" is not something it needs to be taught. The data processing is already baked in.
- goatlover 9y ago
  The point is that being "baked in" is something machines lack which biological intelligences possess. Animal brains don't learn those "baked in" abilities. We may need to "bake in" similar abilities into the AIs, since we recreating evolution is computationally prohibitive.
  - pixl97 9y ago
    >since we recreating evolution is computationally prohibitive. You don't see what you did there. The only way to 'bake in' these things is to create them via evolution in the first place. Also, these instincts are not 'baked' they continue to evolve with each generation.
  - runeks 9y ago
    > The point is that being "baked in" is something machines lack which biological intelligences possess. I’d say it’s the exact opposite: A freshly born CPU is as a capable as it will ever be. The problem is that it never learns anything new, as opposed to biological organisms which continuously adapt to their environment.
    - xapata 9y ago
      Once the CPU runs a chip factory, it'll be able to adapt in a sense.

dgreensp 9y ago

I think it’s really important to distinguish 1. pure problem-solving (chess, go) from 2. competency of behavior in the world (vision, navigating a maze), from 3. universal cognitive-emotional life (getting frustrated trying to accomplish a goal and trying a different approach; having competing drives that form the basis for goal-setting, like hunger, boredom, and self-preservation), from 4. more arbitrary-seeming, human-like cognitive emotions, like humor and beauty. You can have 1 and 2 without anything directly resembling human intelligence, and 3 with animal-like intelligence, or you could make something completely alien. An appreciation of humor and beauty would be a great way to demonstrate you’ve made something like a virtual “human mind.” There’s no reason computers couldn’t be better at all of these things, including writing better jokes. There’s a funny blog post somewhere about the idea of a computer writing superhuman-level funny jokes; I wish I remembered where!

GuiA 9y ago
3 and 4 are pretty hard to beat though, because humans have decades and decades of input and feedback loops with other humans to develop them. Who’s gonna play hide and seek and read bedtime stories every night to the computers?
- dgreensp 9y ago
  “Embodiment” is most important for 2, and to fool humans into thinking you are a real human (as in the Turing test), able to talk about the human experience and relate to other humans. Animals (including humans) are born with a version of 3 (and 4). Emotions are simple. Thought-level nuance is learned over time, but data learned by one android (or whatever) can be shared. Also, children are able to learn from comparatively few data points, and computers are beginning to do this too (see “one-shot” learning, learning from one occurrence, like the way kids sometimes pick things up). If you make a child android that looks and acts like a child, people will read to it and play with it; there are movies about this! :)
  - dgreensp 9y ago
    It would take a lot for a computer to write a beautiful novel, say. But not to appreciate and create beauty in other ways. And I really think computers could write some excellent jokes along the way to becoming more human. Pretty much anything they learn to do can be used for comedy. Physical movement with “character” gone wrong leads to physical comedy. Common-sense knowledge leads to common-sense comedy (like the joke about the elephant leaving tracks in the butter dish, which kids of a certain age find funny but adults seem to have grown out of).

arikrak 9y ago

This is not at all how computers play chess: > A computer can beat a human at chess not by searching for the satisfaction of making an elegant move, but sifting through millions of previously played games to see which move is more likely to lead to victory.

deleted 9y ago
[deleted]
xapata 9y ago
Not historically for chess, but it's a reasonable analogy for how AlphaGo plays Go.
ubernostrum 9y ago
A lot depends on the era you're talking about, for computer chess. It used to be that forcing a chess computer out of its "book", so that it had to start relying on move-tree searches much earlier in the game when that tree is still monstrous in size, was a good or at least OK tactic. As the computers got better, and as more effort was put into anti-anti-computer tactics, it stopped being useful, but to say that this is "not at all" how computers have played chess is incorrect.
- yesenadam 9y ago
  And it's also not what they said.

danielam 9y ago

I thought the beginning of the interview showed promise, but toward the end the conversation unmoors from the topic at hand. I really do wonder how many in the field of AI take as philosophically unsophisticated of an idea like intelligent computers seriously and see it as an obvious and uncontroversial possibility. What Hofstadter is dancing around is that intelligence requires semantics and semantics is exactly what computers, by definition, lack. Knowledge is semantic in nature and thus computers cannot, strictly speaking, know anything. They cannot reason because, again, reason requires semantics. Now, we are able to model and then formalize some domains of reality under some aspect well enough such that computers can behave in very useful ways, but no matter how sophisticated such programming gets, it cannot somehow magically cross over into semantics. The notion is patently absurd. So to say that AI is, literally, far from being intelligent is like saying the color red is far from being a strawberry. No amount of red will ever amount to a strawberry. P.S. I was reminded of this post about Sphex wasps and intelligence, with mention of Dennett and Hofstadter: http://edwardfeser.blogspot.com/2013/12/da-ya-think-im-sphexy.html http://edwardfeser.blogspot.com/2013/12/da-ya-think-im-sphex...

jedharris 9y ago
Please explain how to tell if some being "has semantics". Suppose we encounter some alien made out of crystal and metal, but arranged in organic looking structures. We work out how to communicate, rather roughly (like Google Translate). They won't talk about their ancestors so we don't know if they were built or evolved. How do we find out if they have semantics?
- danielam 9y ago
  Computers aren't a black box mystery. We understand how they work. We understand that they are implementations of Turing machines (or similar computational models), and Turing machines are by definition a formalism and thus syntactic in nature. Computers are therefore no more than syntactic machines (I would further claim that computers aren't strictly speaking syntactic machines either, but physical artifacts -- and we can use different physical properties and states toward this end -- that simulate a formalized, syntactical system). Syntax as such is semantically blind, so to speak. Human beings, on the other hand, do "possess" meanings. We have concepts. Pure syntax can never amount to a single concept anymore than purely speaking about climbing Mt. Everest ever itself amounts to actually climbing Mt. Everest. Any semantics we associate with computer programs is entirely an act of interpretation on the human end.

lisper 9y ago

Something often missed when talking about GAI is that we humans are built by our genes in order to facilitate their (not our) reproduction. Genes don't care about anything, not even reproduction (except in the sense that water cares about flowing down hill), but one of the tricks they use to advance their "agenda" is to build brains that do care about things. A lot of what we call "intelligence" is actually a side-effect of caring about things more than it is evidence of thinking. In particular, it's a side-effect of caring about the kinds of things that advance our reproductive fitness. For example: Hofstadter laments that, although computers can now trounce the best humans in chess, they don't look for "elegant moves" or decline to play and have tea instead. Hofstadter cares about these things because chess is more than an abstract mathematical construct. It is, like all sporting events, a social construct, one that distills the essence of competition where the participants care about who wins and who loses. And all of this derives from evolution where genes that build brains that care about winning competitions outperform genes that don't. One of the things holding back computers from being GAIs is that we have not yet figured out how to make them care about anything, and so they cannot possibly understand the visceral difference between winning and losing, or the emotional angst of being up against a deadline or deciding to take a risk. All of these are part and parcel of everything we humans do. The ability to do math is just an interesting and useful side-effect, but it was never the main event. Personally, I think it's a good thing that we don't know how to make computers care about things because once we figure that out they really will become potentially dangerous. Our desires are hard-wired into us by our genes. Once computers have desires of their own, their interests may align with ours, but that's not a given. And if they don't, that could be a really big problem.

galaxyLogic 9y ago
True, but it's good to keep in mind that genes don't have an "agenda" either. They just are the way they are because they survived. It's like having a neighbor who just won $100 million in lottery and thinking, vow, what is his secret? How could he do that? I don't think I could ever do that. How did he do it? The fact is he didn't have much to do with it, it was all pure chance.
- 9y ago

sonink 9y ago

> What frightens me is the scenario of human thought being overwhelmed and left in the dust. Not being aided or abetted by computers, but being completely overwhelmed, and we are to computers as cockroaches or fleas are to us. That would be scary. I suspect our expectation of GAI is unreasonable and we will sooner or later have to reconcile it with a different and less anthropomorphic expression of intelligence and consciousness. It might not be required for AI to be (anthrophomorphically) intelligent or conscious for it to 'take over'. Infact it might be a huge advance over mankind that it is not.