When the Machine Started

See also:
http://www.sigmaforum.org/

I suggest that these are all happening at once. Good sci-fi takes *one* aspect of society and exaggerates it. Real life is more complex.

Bertram/Cohen + Cowen/DeLong/Krugman = bread and circuses, no?

“The proles are obliged to consume and use up extravagant amounts so as to use the goods up” = current obesity crisis, too.

I misplaced the end of the blockquote in the above post. It should go all the way to the end.

And then there is William Cobbett’s Letter to the Luddites (1816), an excerpt from which I quote below:

I shall now return to the subject of machines, and beg your patient attention, while I discuss the interesting question before stated: that is to say, whether machinery, as it at present exists, does, or does not, “operate to the disadvantage of journeymen and labourers.”

The notion of our labourers in agriculture is, that thrashing machines, for instance, injure them, because, say they, if it were not for those machines, we should have more work to do. This is a great error. For, if, in consequence of using a machine to beat out his corn, the farmer does not expend so much money on that sort of labour, he has so much more money to expend on some other sort of labour. If he saves twenty pounds a year in the article of thrashing, he has that twenty pounds a year to expend in draining, fencing, or some other kind of work; for, you will observe, that he does not take the twenty pounds and put it into a chest and lock it up, but lays it out in his business; and his business is to improve his land, and to add to the quantity and amount of his produce. Thus, in time, he is enabled to feed more mouths, in consequence of his machine, and, to buy, and cause others to buy, more clothes than were bought before; and, as in the case of the ten sailors, the skill of the mechanic tends to produce ease and power and happiness.

The thrashing machines employ women and children in a dry and comfortable barn, while the men can be spared to go to work in the fields. Thus the weekly income of the labourer, who has a large family, is, in many cases, greatly augmented, and his life rendered so much the less miserable. But, this is a trifle compared with the great principle, upon which 1 am arguing, and which is applicable to all manufactories as well as to farming; for, indeed, what is a farmer other than a manufacturer of corn and cattle?

That the use of machinery, generally speaking, can do the journeyman manufacturer no harm, you will be satisfied of in one moment, if you do but reflect, that it is the quantity of the demand for goods that must always regulate the price, and that the price of the goods must regulate the wages for making the goods.

I think, then, that it is quite clear, that the existence of machinery, to its present extent, cannot possibly do the journeyman manufacturer any harm; but, on the contrary, that he must be injured by the destruction of machinery. And, it appears to me equally clear, that if machines could be invented so as to make lace, stockings, &c. for half or a quarter the present price, such an improvement could not possibly be injurious to you. Because, as the same sum of money would still, if the country continued in the same state, be laid out in lace, stockings, &c., there would be a greater quantity of those goods sold and used, and the sum total of your wages would be exactly the same as it is now.

But, if machinery were injurious to you now, it must always have been injurious to you; and there have been times, when you had no great reason to complain of want of employment at any rate. So that it is evident, that your distress must have arisen from some other cause or causes. Indeed, I know that this is the case; and, as it is very material that you should have a clear view of these causes, I shall enter into a full explanation of them; because, until we come at the nature of the disease, it will be impossible for us to form any opinion as to the remedy.

Your distress, that is to say, that which you now more immediately feel, arises from want of employment with wages sufficient for your support. The want of such employment has arisen from the want of a sufficient demand for the goods you make. The want of a sufficient demand for the goods you make has arisen from the want of means in the nation at large to purchase your goods. This want of means to purchase your goods has arisen from the weight of the taxes co-operating with the bubble of paper-money. The enormous burden of taxes and the bubble of paper-money have arisen from the war, the sinecures, the standing army, the loans, and the stoppage of cash payments at the Bank; and it appears very clearly to me, that these never would have existed, if the Members of the House of Commons had been chosen annually by the people at large.

The bleeding obvious example you have missed is Huxley’s “Brave New World”, which was all about engineering society to mass Fordist consumption/production parameters.

I assumed there was some manner of taboo in the other thread against going the obvious sci-fi route.

Early Vonnegut–Player Piano–and Philip José Farmer’s “Riders of the Purple Wage” are two that resonated for me back in the day. You are probably quite aware of them, however.

Consider the fraction of clerical work that essentially consists of a person reading from one computer generated report and typing it into another computer. Computerization has greatly reduced the amount of internal paperwork corporations generate but have significantly increased the amount of paper exchanged between them.

Another major source of inefficiency is needless duplication of bureaucratic forms. When taking a job or enrolling a kid in school one can easily spend two or three hours filling in thirty plus forms, every one of which requires a full name address, social security number, etc. to be entered at the start.

The next phase of the Web is Web Services and they will enable direct transfer of information from one computer to another in machine readable form. Even a simple step such as automating the invoicing process would realize considerable savings.

Who do you think you are, John Holbo?

Cory Doctorow, After the Siege: Completely automated manufacturing makes it possible for people to freely duplicate almost any material goods. Nations that allow their citizens to do so get bombed and invaded by corporations/governments who claim ownership of the duplicated goods.

Charles Stross, Accelerando: Earth and the rest of the inner Solar System is devoured by incomprehensible AI that is the descendant of legal/financial software. A lot of other stuff happens too.

Ken MacLeod, The Stone Canal and The Cassini Division: Posthuman intelligence proves incomprehensible and hostile. There are two major factions of humans, one left-libertarian and one right-libertarian. Both develop postscarcity economies. The right-libertarians have cooler technologies in a few ways, but they also manage to reinvent slavery (of intelligent machines and mind-uploads) and nearly exterminate humanity when they try to open commercial relations with the posthumans.

Ken MacLeod, The Sky Road: A diverging future history connected to The Stone Canal and The Cassini Division, but very different from them. Post-singularity technology is ubiquitous, but generally low-energy and benign. Earth’s inhabitants are secure, peaceful, prosperous, and in no hurry to go to the stars. Not much happens, but enjoyable for the technological and social daydreaming; like Edward Bellamy for eco-conscious computer geeks.

Also, Charlie Stross’ Glasshouse for a look at a climax post-scarcity culture and the evils that still affect it. And a classic from back in the mid-20th Century, Damon Knight’s A for Anything: the birth pangs of post-scarcity economy when matter duplicators remove the need for manufacturing.

As for strong AI, it will probably happen eventually, but it’s going to take a lot longer than the researchers have been predicting. What AI has been good for in the last 50 years is finding out what intelligence isn’t. Not to say that’s not useful, but it wasn’t what the enthusiasts were hoping for.

http://en.wikipedia.org/wiki/Karel_%C4%8Capek

The word robot comes from the word robota meaning literally serf labor, and, figuratively, “drudgery” or “hard work” in Czech, Slovak and Polish.

The original and still the best.

What a coincidence — I just finished my second reading of Stross’ Accelerando last night. The intelligence of the AIs he postulates are to our intelligence as ours is to the nematode worm.

So, when a nematode worm writes science fiction about humans, what does it talk about?
1) other nematode worms with which it would like to exchange genetic material;
2) how to avoid getting stepped on by humans;
3) the evil of nematophagous fungi;
4) talking to the one or two humans (out of billions) who for some inexplicable reason are interested in nematode worms and don’t step on them on purpose, and;
5) raising the next generation of nematode worms.

It’s a great book, just that postulating beings faroutside our ken means…they’re just too outside our ken! (I had a somewhat similar reaction to to Nivens’Ringworld series.)

Fritz Leiber, “The Silver Eggheads”, where the machines replace artistic work (writers) instead of manual work and robots have unions and so on.

Also, “Star Treck”, where a tool, the replicator, can produce everithing so that nobody does any productive work but everybody is then part of the army and embarked in a thinly disguised imperialist enterprise (militay keynesianism!).

Well that’s also because computers win chess through brute force methods.

I’m pretty sure at least some of them have a self-learning component, though.

Most of the other problems solved by AI, are actually algorithmic, probabilistic or statistical solutions to problems that humans manage in very different ways. Usually things for which humans didn’t evolve, and so our solutions are pretty suboptimal. Yes all kinds of things, usually very boring things (the legal and financial work that’s being computerised is extremely tedious) that requires very little creativity, or imagination.

Again, I think this is a rather limited view. Computer software exists that can compose orchestral music that passes the Turing test: i.e. even musical experts can’t tell which pieces were composed by machine and which by humans. The whole “machines can’t be creative” argument is a bit 70s.

Nancy Kress “Beggars in Spain” and sequels, although there an important (central) aspect is human augmentation, but it ends up in a world where the vast majority or “normal” people are paid by the State to live lifes of absolute apathic leisure. Why do anything when a – energy is ultracheap, so everything is cheap and plentiful and b – there real truth of the world is that you Normal Proletarian are not capable of understanding anything at the level that Genetically Modified Genious (substitute for AI here if you like) do, so why study, create, or participate in politics?

It has some libertarian vibes that I dont know if are meant to be exalted or ridiculed or both things but leave me a bad aftertaste after reading it.

Cian, this is not true. Brute-forcing a noughts and crosses game is dead easy and can be done with pencil and paper. (here http://xkcd.com/832/) Brute-forcing a game of draughts is not so easy but can be done if you have a few years. (http://news.bbc.co.uk/1/hi/sci/tech/6907018.stm) Brute-forcing chess is orders of magnitude more difficult and has not yet been done at all, because it has about 10^45 possible positions.

I think that this is right tho’ in that chess machines just try things, they don’t have much intuitive play. Also, I think it is incorrect to say that machines can compose; rather, we know how to compose aleatory pieces that machines can implement.

Brute-forcing chess is orders of magnitude more difficult and has not yet been done at all, because it has about 10^45 possible positions.

Okay put it this way. It uses clever programming techniques that while making it tractable, rely heavily on brute force. Despite this, it can almost be beaten by a human being with very limited processing resources (short term memory/processing speed). Human beings and chess playing computers do not play in a similar fashion, which is how it is possible for a grand master to sometimes beat the world’s best chess computer.

Go is harder because there are more possible moves, but given enough time/computer power and research into programming techniques (which is where much of the intelligence comes from – the designers) it too will be solved and there will be a computer based world champion. Doesn’t get us anywhere closer to AIs running the world though. Anymore than a computer which can solve sums really fast does, or a computer that can fetch more records in a second than an office full of clerks could in a year.

What much of AI is good at is finding alternative ways of solving problems that humans can do, that do not require all the extra machinery of human intelligence. They are like a human being in the sense that a spinning jenny is. I think that’s a real achievement, important, but it has real limitations. And its dependant upon extremely smart and gifted programmers to encode all this stuff in the first place.

There are other styles of AI that are more successful in the real world, though they essentially work by mimicing animal intelligence (they’re embodied, use neural networks that are loosely patterned on the way that animal’s/insects/humans work). But they’re a long way from being able to replace us, though they might be able to replace a cleaner/driver in the not too distant future.

Again, I think this is a rather limited view. Computer software exists that can compose orchestral music that passes the Turing test: i.e. even musical experts can’t tell which pieces were composed by machine and which by humans. The whole “machines can’t be creative” argument is a bit 70s.

You can write software to write pastiches of particular composers, or styles. Its basically a form of algorithmic, or aleatory, composition. To my mind a not hugely interesting one (at least musically. The analytical work required to achieve it can be pretty interesting). You can also use both neural networks and genetic algorithms as filters on the compositional process to winnow out more interesting pieces, but the actual training is conducted by a human being. There’s no self-directed learning.

There’s also some visual art that’s generated this way, but again its just pastiche. Then there’s the poetry…

I’m sceptical of the idea of the machines taking over in the good old fashioned strong AI sense too, and not over anything as silly as qualia. I think the moving goalposts argument for AI is a good one: As soon as we figure out how to make a machine do it, it doesn’t seem so smart anymore. The thing is, I think this implies a defintion of intelligence that contradicts the adjective “artificial.”

If we ever manage to build a machine that’s really capable of taking over, we’ll have so replicated the human reasoning process that it will no longer be artificial in any real sense. At which point, it’ll probably veg in front of the TV and get drunk at the pub like the rest of us rather than conquer the world. Until then, AI is just like the mechanical thresher: An extension of human abilities rather than an autonomous intelligence.

C.B. @23
I believe that Rosa Luxemburg had a pithy phrase expressing the choice between these alternatives.

Unfortunately, some of us (or perhaps I should just speak for myself) suffering from less-than-great memories or cognitive overload or less-than-complete educations in the history of radicalism (or all three) remember offhand only one R. Luxemburg quote: “If I can’t dance I don’t want to be part of your revolution.” [printed on numerous T-shirts at one time and attributed, possibly wrongly, to RL]

32: there’s a difference, I think, between aleatoric music and what these programs are doing. It’s not just randomly recombining a list of musical phrases, it’s creating new pieces in the general style of a given set of input pieces.

The issue is the transition from input to output; I think that the art content of that transition arises when the rules are laid out, not when they are followed.

But of course this is a moving goal post: the point is the changing border of art and craft, and changing notions of creativity. Descriptively, if a machine can do it, it isn’t creative. There’s a definite reluctance to let machines do art.
But a machine would never write 3’44’ ‘. That’s a problem. (The spectre of intentionality.)

the point is the changing border of art and craft, and changing notions of creativity. Descriptively, if a machine can do it, it isn’t creative. There’s a definite reluctance to let machines do art.

This is very true.

But a machine would never write 3’44’ ‘. That’s a problem.

It’s a problem for a lot of art: most music isn’t as innovative as 3’44” and yet it’s still classed as creative. Haydn emulated Mozart’s style in a lot of his pieces. Does that mean that he wasn’t a creative artist? If he’d done nothing but churn out Mozartish music, he wouldn’t have been a great composer, but wouldn’t he still have been a creative artist?

32: there’s a difference, I think, between aleatoric music and what these programs are doing. It’s not just randomly recombining a list of musical phrases, it’s creating new pieces in the general style of a given set of input pieces.

Its a stochastic process. Granted the algorithms being used are more sophisticated by virtue of having a computer to use, rather than some simple rules in a book, but its essentially a progression of the same idea. I think it shines an interesting light on what creativity is and isn’t (there are definite limitations, which are clear if you’ve ever played around with this kind of stuff, which I have). But all creative people use rules, processes, etc – the fact that computers can both automate and extend this isn’t surprising to me. But I don’t really consider that (as somebody who uses them myself) “creative” exactly. They’re tools that get you further along.

And the stuff is original, but its definitely a pastiche, and its possible that it works partly because people are familiar with the original oeuvre (i.e. it sounds familiar). I’m kind of doubtful that you could write a program that composed like Mozart if Mozart hadn’t already existed. BBCut is a program that generates DrumN’Bass style breakbeats, but somebody invented the idea first.

Its also really just a progression of something that’s been going on for a long time. Most music is essentially algorithmic, or at least rule based (rules for what works, what doesn’t), much of the creativity came from the way that artists challenged, tested and experimented with these. I don’t know of any composition software that does this in a particularly interesting way. And I think it would be quite hard to do so, as it would require a computer system that could hear/feel music like /we/ do. And that goes even more so for stuff like poetry and visual arts.

Deep water here on the nature of human intuition…

There’s a reasonable definition of what that means in practice, so less so than you’re implying.

“It doesn’t count because they’re trained by humans”… most human artists are also extensively trained by humans!

And some of them go beyond their training and produce something original. Computer software doesn’t currently.

I think the problem with both the term “intelligent” and “creativity” is that they’re not very well defined. The first is defined as “stuff humans do”, the second as “stuff creative people do”.

Neither are terribly good definitions when you get down to it.

Cian

The idea that we can’t replicate intelligence artificially seems strange to me – there is nothing magical about human intelligence, it is a continuation of the cognitive abilities of other animals, as we know that other animals can solve problems, use tools, and communicate. Perhaps using a digital silicon based system is not the way we get to replicate the complexity of our synaptic system and its complexity, but there seems no reason to state that we won’t get there eventually.

Also, and this is to bring up an issue that Lem brought up – would we even know AI when it came into existance? The Turing test, the idea that intelligence can be seen when a machine can fool a human, is well, very anthropomorphic, but our intelligence can’t be separated from our past, from the reality that we are social apes and thus still at the base think like social apes. Why would true intelligence in say a collective being (the idea of the intelligent ant or bee colony) or a machine be like human intelligence? To assume that we have a monopoly on what intelligence can be or how it would work and think is also a bit silly to me.

Another pedantic and humourless corrective comment:

>The Bertram-Cohen-*Marx* thesis

that should be

The Bertram-Cohen-Marx-Proudhon thesis…

Proudhon, System of Economic Contradictions: Chapter IV

“What the economists ought to say is that machinery, like the division of labour, in the present system of social economy is at once a source of wealth and a permanent and fatal cause of misery”

and:

“very far from freeing humanity, securing its leisure, and making the production of everything gratuitous, these things would have no other effect than to multiply labour, induce an increase of population, make the chains of serfdom heavier, render life more and more expensive, and deepen the abyss which separates the class that commands and enjoys from the class that obeys and suffers”

His solution? Replacing wage-labour and the hierarchical capitalist workplace with workers’ associations — System of Economic Contradictions: Chapter V:

“it is necessary to procure for all the means of competing; it is necessary to destroy or modify the predominance of capital over labour, to change the relations between employer and worker, to solve, in a word, the antinomy of division and that of machinery; it is necessary to ORGANISE LABOUR: can you give this solution?”

A position, needless to say, libertarians like Bakunin, Kropotkin, Chomsky, follow.

Even if you had an autonomous intelligence, you really wouldn’t want to use it on that. It would get as bored as the rest of us.

That’s another interesting point: is the capacity for boredom really an essential part of intelligence? Or would it be possible to build an AI that found legal documents really, really interesting and liked nothing better than spending all its time going through them?

Cian@44: Even if you had an autonomous intelligence, you really wouldn’t want to use it on that. It would get as bored as the rest of us.

I find the implicit anthropomorphism in the second statement to be rather misguided. To do the task well does require some relatively sophisticated model of human motivation, but no reason that it would need to be linked to the computer’s “motivation”.

In Banks’ novels I believe there is an official intelligence classification system that allows machines of sufficiently low intelligence to be treated functionally differently

This is one of the more troublesome aspects of Banks’s novels (I would say of the Culture, but unlike other problematic aspects of the Culture Banks really doesn’t explore this very much). The supposedly low/restricted intelligence AIs in the novels seem to me to be very close to, if not at, the philosophical zombie stage of AI. They have minds at least sufficient to understand human language with a lot of nuance (which in turn suggests a fairly sophisticated theory of mind). Is it possible to thave that without the trappings that would make enslaving a sentient being morally wrong? Alas, it doesn’t seem to be something that Banks is all that interested in. He’s rather more amused by the conceit of the higher Minds benignly tolerating humans.

@52:

You’re correct that Banks doesn’t spend much time investigating this issue, but it’s a really hard one! In general, determining when an AI becomes ‘real’ is not a question anyone actually knows the answer to and Banks just doesn’t try to address it, imo. But he also doesn’t create any moral dilemmas. A knife-missile may be capable of complex language processing, but it really isn’t represented as a being. On the other hand, the really stupid AI running a shuttle craft in one of his stories is represented as being a respected (by the Culture at least) person. Banks sort of posits a clear dividing line between AI and not-AI without really getting into the question of whether that is feasible.

What I was meaning to say and just sort of forgot to is that it’s tough to criticize an author just because they don’t want to get involved in an issue you’re interested in. SciFi is about asking questions about humanity under certain technological conditions. But the author gets to choose what issues he wants to investigate.

ajay @ 48:

We seem to be able to create humans who find legal documents really interesting, so I expect creating AIs that do so won’t be an insurmountable problem. But the ethical issues are very similar, and have been treated for the human side of the question in Vernor Vinge’s A Deepness in the Sky, where it is possible to turn neurotypical humans into what amounts to autistic spectrum individuals. The ethical question here of course is when, if ever, is it permissible to treat humans as machines, as objects? And the dual question is, when, if ever, is it obligatory to treat machines as humans?

Right now I’m reading Alone Together by Sherry Turkle, in which she confronts the question of how humans do, and how we should, relate to affective robots head on. It’s a fascinating and somewhat scary book.

Banks sort of posits a clear dividing line between AI and not-AI without really getting into the question of whether that is feasible.

ISTM that the presence of the “A” in “AI” doesn’t really affect this question, except contingently. The real problem is deciding whether intelligence (in the relevant sense) vs. non-intelligence can be clear-cut, and if not, how your ethical or legal system should reflect that. Because the fact that no edge cases currently live on Earth (if, indeed, you don’t think that nonhuman apes are an edge case, or humans with certain mental disabilities, or humans at certain stages of cognitive development) isn’t something we can rely on in all possible future circumstances.

If the designation of “intelligent” is vulnerable to the paradox of the heap, then what? I picture someone trying to explain that a line has to be drawn somewhere, even if it seems rather arbitrary, to a being that falls just on the wrong side (although, if such an explanation is possible, you may have misclassified the being in question).

But the ethical issues are very similar, and have been treated for the human side of the question in Vernor Vinge’s A Deepness in the Sky, where it is possible to turn neurotypical humans into what amounts to autistic spectrum individuals.

Moon’s _The Speed of Dark_ contemplates the reverse operation. It might be interesting to compare their approaches.

Also: what happens if artificial intelligence is intelligent, but in a way at least as different from neurotypical *and* autism-spectrum humans as they are from each other, or even more so? Most of our species has basically no familiarity with communicating with beings whose minds function substantially differently from their own (autistics and their close acquaintances being arguable exceptions).

mpowell @ 47 wins the thread! (By explaining the hidden agenda behind computer scientists’ insistence that most of what “AI” can now do isn’t “really intelligent”: they are just trying to keep their creations from being protected by humanitarian considerations, and are not to be trusted.)

Actually, I was nonplussed to read on Wikipedia that Banks thought of his world as a left alternative. Dreaming up the Culture strikes me as something a rightward leaning person is more likely to do (though I’m not sure I can justify this feeling).

Also, no one is saying, “You people aren’t able to do anything more complicated than sort through legal documents with 90% reliability, therefore we consider you to be AIs with no rights.” They may be saying, “Therefore, you are not going to be hired as associates,” or even, “Therefore, you will be hired as temps, and therefore, you will not receive health benefits.” It isn’t the same thing at all.

You don’t need to give machines “true” autonomous intelligence and creativity (whatever that may be) for them to render conventional economic structures obsolete. If the only jobs left for humans are those as creatively demanding as composing new pieces of music in an original style then the number of humans still employed in 100 years’ time can comfortably fit in a single football stadium.

Don’t get too hung up on the example, but if you take music that’s probably the jingle writer and generic film score writer. Or in pop music the guy who writes the music for boybands (Girls Alive would probably be okay though). How much of law would be wiped out by programs that can find relevent documents?

There’s a bit difference between rendering conventional economic structures obsolete, the kind of scenario that Krugman describes though. The industrial and agricultural revolutions rendered conventional economic structures obsolete, destroying the majority of human occupations. And yet here we are.

The humans provided guidelines to the program, but the actual design doesn’t look like anything those NASA engineers or any other human engineer would have designed by hand. It looks more like part of a plant than any traditional antenna shapes, it outperforms traditional antenna shapes on all figures of merit, and it was faster to develop too.

This doesn’t surprise me, but this is essentially (well okay not really, but good enough for the purposes of this argument) a brute force solution to a tractable well bounded problem (like chess). Its using the strengths of a computer (processing speed, ability to be very repititive) and combining it with some clever algorithmic stuff to get round the NP completeness issues (good enough, rather than perfect – mating, etc). And its a well bounded problem because human beings have worked out the constraints, and they’re not too complex.

Computers are good at that stuff. What they’re not good at is wicked problems, which is what much of design is, because that involves playing with, exploring, testing, etc constraints. I suppose that might change, but there’s little sign of that on the horizon. So the genetic algorithms here are very sophisticated, but they’re still another tool. We’re a long way from having the shuttle being designed entirely by a computer.

A new form of intelligence will probably be *vastly*, unimaginably different from our own, so much so that we won’t recognize it as “like us.” We’re not talking about the intelligence of a normal human vs. an autistic human, or even a normal human vs a smart chimp, we’re talking the intelligence of a normal human vs. the intelligence of an anthill with symbiotic fungi, or vs. the intelligence of the vertebrate immune system, if those things were competing with us in the realm of economics or technology where we perceive that our kind of intelligence is important.

It’s worth thinking about places where we run into adaptive, learning kinds of behavior we have a hard time overcoming. Think about pathogens or pests evolving around our attempts to control them. It’s not intelligence anything like we normally think of, and yet it adapts around our development of antibiotics and disinfectants, or around our antivirals, or our insecticides, as though it were a thinking system beating us at some complicated war game. I have the sense that competing with an AI would have that feel.

@71: Oddly most of that stuff tends to be a result of a few simple rules interacting. Its amazing how simple the rules are that control flocking behaviour in birds for example. Or for that matter the behaviours of insects. You can do a lot of stuff that we think of as requiring intelligence, and which is quite hard for us, with a few simple rules.

@Cian @70

The point is about productivity, not China.

You’d look smarter declaring people as not knowing what they are talking about if you actually read what was said.

Cian@64: The idea that you could have a non-emotional creature that functions like humans do seems fundamentally misguided [emphasis added]

Oh, I absolutely agree and for the tasks under discussion I never assumed that the computer would function like a human. I’m right with albatross in 71 on what the they are liable to be “like”.

“The question is,” said Humpty Dumpty, “which is to be master–that’s all.”

Arrgh, try again:

@74: Consider a box. Suddenly after 5 seconds a light comes on. Is this the result of a human intelligence? Or a random element? Could be either. In and of itself its no demonstration of intelligence, despite the fact that the person inside the box might be Beethoven. The mistake here is to think that just because an intelligent person does something, the activity itself requires intelligence. Or that the activity can only be done in a way that requires intelligence. Which is essentially the mistake made by AI proponents for nearly 60 years now. Nobody thinks a computer is intelligent because it can divide 1032424 by 32. But that’s something that humans used to do all the time.

Or to put it another way – once the person emerging from the car can do other things.

As it happens we’re probably quite close to that car being at least theoretically possible. And yes I think it demonstrates a rudimentary form of intelligence much like you’d find in an insect (but nowhere near what you’d find in a crow). Its a long way from that to the human driving the car (and probably not as well as the insect brain). Its a huge leap from that to the kind of stuff that people are talking about on this thread. Nor is an insect brain likely to make many white collar workers redundant.

As soon as we figure out how to make a machine do it, it doesn’t seem so smart anymore.

“When a measure becomes a target, it ceases to be a good measure.” —Goodhart’s law.

Similarly, any distinguishing characteristic which becomes a target for convergence ceases to be a good basis for distinction. In particular, most any definition of intelligence in terms of performance capability will become obsolete over a sufficiently long time horizon (and with good riddance, because it wasn’t a terribly good definition in the first place).

People have a bad tendency to assume that intelligence is possible with a conventional computer, but there’s no evidence for this. […] What they’re not good at is wicked problems, which is what much of design is

Not just design. A large proportion of intractable-until-solved abstract problems were rendered tractable by an insightful reformulation of the question or hypotheses.

If we define “intelligence” as “the capacity to learn how to do things you weren’t initially certain you were capable of doing, relatively quickly and with relatively minimal guided instruction” then various specialized robot overlords likely have us matched within the century, and if we define intelligence as “the ability to reformulate characterizations of phenomena in frameworks which render previously tractable problems solvable” then there’s not much sense in calling it a human trait.

@ScentOfViolets,
The estates might be explainable by the fact that I don’t remember them at all, but do remember the “caves of steel,” the overcrowded apartment towers and communal dining halls, and the elaborate system of conveyor belts instead of subways.

I just don’t think it [an AI achievement] demonstrates anything significant about true intelligence. – Cian @34

The phrase “No True Scotsman” comes to mind. Which is exactly the point AI proponents make when they say that when a maqchine does something we tend to declare it cannot be “true intelligence” by definition.

@ajay: When you can point me to a cd of music composed by a computer that has the same emotional impact on me that first hearing a Beethoven of Mahler symphony had, then I’ll be impressed. A few years ago some guy embarked on digital renditions of classical works by taking literally a note here a note here from all the best recordings of these works to make a perfect performance of a given work. Had a demo up on the web that challenged you to tell which was an actual human conducted work and which was put together. I aced it four for four. May happen, but I’m not holding my breath.

When you can point me to a cd of music composed by a computer that has the same emotional impact on me that first hearing a Beethoven of Mahler symphony had, then I’ll be impressed.

This sort of thing seems unfairly set up. Why should we compare fledgling artificial intelligence to the sort of people you would presumably uphold as among the greatest geniuses of all time? We don’t demand that of people, and humans as a species do have quite a head-start. A more reasonable standard might be, can I [someday] point you to a CD of music composed by a computer that you’d respond to with a, “say, that’s not bad, who is this?”

Consider:

Watson, the Jeopardy!-playing supercomputer, did give the right response. In a way. The clue, in the category “Rhyme Time,” was “A hit below the belt.” Though this was just a practice round, held years before the public man-vs.-machine challenge that airs this week, Watson was dealing with authentic game-show material. Back in 1992, when human contestant Marty Brophy saw that $200 stumper in a broadcast episode, he correctly replied, “What is low blow?” The state-of-the-art AI, by contrast, scanned its elephantine database of documents and came up with something else: “What is wang bang?“

So, yeah, teach a computer to think and communicate and innovate somewhat like a human, and the first thing it comes up with is a dick joke. Give the poor things a little time to mature…

I would also note that computers have produced truly original designs, not preconceived by their creators or by any other humans, in the domain of machine-design. NASA has been using evolutionary programs to design optimized antennas for space missions for 5 or 6 years.

I used to work bit in this field (not antennas, but similar optimization techniques for aerodynamic shapes). You might call it intelligent, though I am more in Cian “tool” camp. But the relevant part here is that it such techniques are not big labour savers.

A big part of engineering design work is defining the problems: what are the targets, how will you make trade-offs between them, what are the hurdles and limitations we will run into, do we understand these limitations, can we model them, if not do we have data from experiment or practice, if not can we create such data or otherwise add a safe margin around the uncertainty?

The other big chunk is interacting with other domains of expertise: you understand your part of the work fairly well, but how will your choices affect other parts? That takes up lots of time, from informal meetings to years-long design iteration cycles.

By the time such issue are clear enough to be turned into computer code, most of the work is already done. Programs can be very useful both in finding a better solution within the defined problem, and in fast communication with other domains. Surpisingly often, their main use is simply documentation: they force experienced designers to cast part of their experience in an explicit form, before they retire or move on to another field.

But the result is almost always better solutions with the same amount of human work, not less work for satisfactory solutions. And because making computer code is rather labour intensive too, the result is often better solutions at the price of more human work.

Might change in future. I don’t have a crystal ball. But right now, the trend is not that computers lead to across the board reductions in people to design stuff.

Salient, but is there any evidence that a computer is about to make the leap independently from pastiche (something for which the rules are fairly well known, and can easily be embedded) to something innovative that sounds good to a human ear. Evenly slightly innovative.

I’m really not convinced, and this is partly based upon my own personal experience, that pastiche leads inevitably to the second. That musical composition is somehow a linear thing from derivative dreck, to genius. We already had music schools that were teaching compositional rules to students, who churn out fairly derivative dreck. That that could be automated doesn’t seem terribly surprising. But we don’t know how to teach innovation, and yet every year plenty of people creative innovative music in a variety of fields.

Best I can see there are two kinds of phenomenon here. The first is the human ability to recognise and learn a pattern, and then consistently apply it. We’re now at the point where we can also teach a computer that pattern (though a human being has to be on hand to train it – hints here perhaps of where the jobs in a new economy might lie) and it can apply it far faster than we can. But we don’t seem to have learned how to do the second thing.

And these compositional tools will inevitably be applied by some nutcase in ways that never occured to anybody who designed them, and some new genre of music will arise. The drum machine and the sequencer were going to get rid of musicians. Never quite happened.

So, yeah, teach a computer to think and communicate and innovate somewhat like a human, and the first thing it comes up with is a dick joke.

Unless one of the programmers put that in deliberately (always pick dick when given choice), total coincidence.

I see the same thing, but interpret it differently: things that marked intelligence 100 years ago still mark intelligence today, even if they can now be done by repetitive logic applied at high speed instead of human brains.

Why did they mark intelligence 100 years ago? What was the criteria?

Again to look at it a different way. Say that there was an operation which used to be very difficult, but then a mathematician found a formula that meant anyone with a high school diploma could do it. Does being able to do this task still denote the same level of intelligence?

Or if we’re using cultural markers. Being able to read and write used to be markers of intelligence. Now not so much. Have we all somehow got more intelligent, or is just that our cultural measures of intelligence were not terribly good?

Rather than keep my conception of intelligence fixed as something which is ineffable and the near-exclusive property of humans, I keep the markers fixed and allow my conception to accommodate any successful completion of tasks that traditionally signified intelligence when performed by humans.

Why? What do you gain from doing this?

Currently we have really poor measures of human intelligence. We don’t really know how to measure it. We know very little about how the brain works. There’s increasing evidence that much of what we consider “cognitive processing” takes place outside the brain – either through the body, distributed through our tools and socially. Given that we know so little, I think making confident pronouncements about what intelligence might be is is profoundly misguided.

Machines are divorced from our evolutionary and social context and their intelligence is task-oriented.

Actually the car you mentioned above is not task orientated, its stimuli/response orientated, just like us. I think we’re so far from the point where computers could even deal appropriately with our social context, that its impossible to say what will happen there.

But the lion’s share of formal economic activity is also rather specialized, repetitive, task-oriented, and not particularly sociable

Is it? Parts of it definitely aren’t, other jobs where you think that would be the case actually have a surprising amount of tacit knowledge, fuzziness, compromise, etc. All things that computers are appaling at. Even something like accounting, which seems like its all hard edges, isn’t really when you look at it closely.

People made this confident predictions before with the IT revolution, yet it never really happened that way for exactly those reasons.

And while it might mean the elimination of jobs, it might equally mean a lot more jobs of a different kind. I mean look at the transformation of accounting, or all the jobs created by the database. The lesson from the Industrial revolution is that massive increases in productivity do not necessarily eliminate jobs, they can simply create new spaces where people are now needed as a consequence of the world created by that productivity.

That said, I think there is an economic problem looming. And that’s that markets don’t seem to be a particularly good way of managing service economies. And as these new technologies promise (perhaps falsely) to bring productivity improvements to service economy that have hitherto only been possible in the Industial economy, that could become a bigger problem.

Brute-forcing chess is orders of magnitude more difficult and has not yet been done at all, because it has about 10^45 possible positions.

This is true if you were talking about brute-forcing a game of chess from beginning to end. However, there are lots of chess-like games (to take a non-trivial example, the game of “queen and pawn versus rook”) which are combinatorially smaller and which can be brute-forced. And I think Cian is right to say that the additional step which took computer chess from “good, but not able to beat grandmasters” to “better than the best human players” was the development of massive endgame databases (someone who knows more about computer chess than me might be able to gainsay this).

Interestingly, successful backgammon programs (which can currently beat most human players but not world champions) don’t look very much like successful chess programs at all; they’re based on neural networks and don’t use leaf-and-branch searches as their main method of analysis. I suspect that further success will be achieved in backgammon (ie, that there’s nothing really intrinsic to the stochastic element of the game or to the nonlinearities introduced by control of the doubling cube which makes it intractable), but they’ll be the result of advances in nonlinear nonparametric regressions rather than anything that looks like “intelligence”.

David in #87 is pretty much bound to end up being surprised one day; there are already machine-generated pseudoMozart compositions which can’t be told apart from the real thing. But but but …

I don’t think that the “No True Scotsman” objection is valid, and I think it’s actually sensible to say that all of these solved problems are not evidence of underlying intelligence. Intelligence isn’t about answering questions; it’s about knowing which questions to ask (there are elements of this in the discussion of 3’44” and of drum and bass – give a computer a musical genre and it can follow the rules, but inventing an entirely new musical genre is a lot more difficult, although I would guess still basically possible as it’s really just more problem-solving).

In other words, I for my part will be impressed when we have a computer that can come up with a convincing criterion for what might constitute a credible test of whether it is intelligent.

Why? What do you gain from doing this?

Currently we have really poor measures of human intelligence. We don’t really know how to measure it. We know very little about how the brain works. There’s increasing evidence that much of what we consider “cognitive processing” takes place outside the brain – either through the body, distributed through our tools and socially. Given that we know so little, I think making confident pronouncements about what intelligence might be is is profoundly misguided.

Again, I see the same thing and draw the opposite conclusion. Since the mechanisms of human intelligence are so poorly understood, and so ill suited for comparing across different organisms or entities, it makes more sense to to me to judge intelligence by outcomes, at minimum outcomes that were widely understood as intelligence-markers before programmable computers made people defensive about what markers should count. I want a collection of yardsticks that don’t change in length all the time. If lifting 200 kilograms is easier now than it was before machines, and understanding a menu in a foreign language is easier now than it was before machines, why should I redefine strength or redefine intelligence to minimize the capabilities of machines? The alternative is as if the story of John Henry came to emphasize that a steam hammer couldn’t run or throw and didn’t use real muscles, therefore it was a cheat with no true strength.

From the other direction: a slide rule “knows” how to calculate cosines, but it isn’t intelligent. Admittedly, if an alien race turned out to have an actual physical analogue to slide rules in their brains, and thus could calculate cosines really well, we would call it intelligent. But we still wouldn’t say a person who looked up positions on a slide rule without any understanding could intelligently compute cosines (even though a slide rule doesn’t model human behavior well in this case just because we can’t compute cosines as well as it does).

Currently we have really poor measures of human intelligence. We don’t really know how to measure it. We know very little about how the brain works.

I’m guessing that ultimately it all comes down to just selection rules operating on what comes out of some process which has random variation built in. Yes, even that much-vaunted “creativity” that so many humanist types go on about.

The switcheroo and the mysticism comes in because the casual observer isn’t privy to all the failures. Yes, instinctual behaviour can be quite complex, in some cases seeming to be miraculously so. But focusing on the behaviour of individual members in a successful ant colony is kind of pointless unless one looks at the trillions of instances where other ants got it wrong and paid the price.

I’m guessing that ultimately it all comes down to just selection rules operating on what comes out of some process which has random variation built in. Yes, even that much-vaunted “creativity” that so many humanist types go on about.

You know you could read the odd book on what we do know, rather than just randomly guessing…

@99: Your argument is basically that you want to use a criteria that is fixed, chosen from an arbitrary point in time before people allegedly got “defensive” about intelligence because of computers (evidence of this forthcoming no doubt) and you don’t care how rubbish, unpresentative or plain wrong it is, just so long as its fixed DAMN IT. A hundred years ago people thought somebody who could add and multiply large sums in their head was pretty damn smart. Why not just use that, its no less arbitrary than anything else. Plus that would really prove that computers are more intelligent than humans.

Well I can’t stop you, but I don’t really see any point continuing the argument.

@104: A top singer probably couldn’t make a good recording of themselves singing. Still a good singer. Your argument might need some work.

There was no special revelation about the human brain or human thought that caused people to conclude that playing world-class chess is an unintelligent activity. It was the triumph of a computer at the task.

Well, technically, there is that one quote of Von Neumann. But his point of view wasn’t widely accepted at the time. He seems to have been right in hindsight, though.

Yes, when a computer offers up River Dance, I’ll be most mightily depressed.

What often gets lost in the noise is that there is nothing stopping a plain old meat bopper from implementing those same algorithms using pencil-and-paper and beating any human who plays chess the old-fashioned way.

Unless there’s a time limit, of course. “In principle” a human with a blackboard can produce a 5 day weather forecast just as well as computers, as long as the human is allowed a million years with a blackboard the size of Greater Los Angeles. Quantity has a quality of its own.

Uh-huh. That’s part of the rules of the game and that’s way playing chess by mail over several a period of months is imp- Oh. Wait. That’s not true.

My point, for people like you who don’t seem to be terribly well versed in the subject is that the distinction between the machine and the algorithm must be kept firmly in mind at all times. This is basic stuff.

The same can be said of any of a number of achievements attributed to machines; in reality, computers are doing nothing more than playing back the the thoughts of a dead man. They are a more sophisticated type of gramophone, playing prerecorded algorithms rather than soundtracks, nothing more.

The people who who created today’s top chess programs could not defeat top human players if they played directly instead of writing programs to play. Top human players could not defeat today’s top chess programs if you gave them access to powerful computer hardware and a software development environment. A good chess program isn’t just a gramophone for chess play or a Wizard of Oz disguise for computer scientists.

Sigh. I had thought that the notion that machines implement algorithms that are put into them by hand would be not only not controversial, but universally known by anyone who would presume to speak with any authority on the subject.

Apparently I was wrong.

I’m guessing that ultimately it all comes down to just selection rules operating on what comes out of some process which has random variation built in. Yes, even that much-vaunted “creativity” that so many humanist types go on about.

You know you could read the odd book on what we do know, rather than just randomly guessing…

Sorry that was unfair. Bad day.

To the contrary, it is painfully evident that I apparently know enormously more than just about anyone else commenting on the subject here. At least, judging by the comments ;-)

You may read “I’m guessing” as “noncontroversial mainstream opinion” if that helps any.

Matt,
SoV is always correct. Its opponents are always snivelling fools, or arguing in bad faith. If you hang around this comment section long enough, you will know this irrefragable truth.

Again, with feeling:

What often gets lost in the noise is that there is nothing stopping a plain old meat bopper from implementing those same algorithms using pencil-and-paper and beating any human who plays chess the old-fashioned way.

Plain old meat boppers, and even the computers of of a few decades ago, are not capable of defeating skilled human players by running modern chess algorithms because they are too slow to play a full game before expiring of old age. A computer implementing algorithms to play chess is not just a recording of old games, a sleight of hand trick for disguising the programmer’s chess skill behind a silicon mask, or something that plain old meat boppers could imitate by hand to win tournaments.

Whether it’s a tournament with time control or not, you have to finish the game in one lifetime. That’s not very much time at all if you propose to win games by stepping through computer chess algorithms with pencil and paper.

I’m not trolling or arguing in bad faith. As proof I admit that I was wrong about your idea of recordings: you originally compared chess-playing machines to gramophones with recorded algorithms, not recorded games.

I had thought that the notion that machines implement algorithms that are put into them by hand would be not only not controversial

Look, I hate to be the one to question you on your qualifications, but — you’re a math guy, right? You did take a neural networking class as part of your undergraduate studies, right? I’m assuming this is somewhat standard material for people interested in computers and maths. Try to recall the stuff about node-weighting and training data.

Roughly/loosely speaking, the whole point of a neural network is to design a computer that writes programs for itself, in a probabilistic rather than deterministic way, so that the end result behaviors are non-deterministic. Like, you can program a computer not just to drive a car, but also to respond to unanticipated phenomena. I remember I had a homework assignment where I wrote a program that let a car teach itself the best way to avoid moving obstacles, by trial and error. It kind of sucked, if I remember correctly,

But to be clear, I didn’t give the computer any instruction about how to avoid obstacles, I just taught it to reward itself whenever it happened to avoid an obstacle, and over time (lots of time) it taught itself (somewhat) to maximize its self-rewarding (maximize is too strong; it learned to not suck quite so badly).

So I’m just not sure what you mean. On a very meta level, it’s kinda sorta true. I mean, if I had never written a program, if I had never given the computer anything to start with, then sure, it’s a box of silicone.

But I didn’t write a program for obstacle avoidance; I wrote a program that said “avoidance is good; collision is bad; badness of a collision is a function of the area overlap and the net velocity (sprites could move through each other); now go trial-and-error and flounder around until you figure out how to do it well.” Awesomely, early on it just slammed on the brakes all the time, and over time it did more swervy type stuff and braked less. I didn’t teach/program it to compute velocities or trajectories other than its own; it just trial-and-errored its way through a field of moving rectangles. A friend of mine in the class chose to teach a van how to parallel park, which was funny because he didn’t know how to parallel park, at all. His program also kind of sucked, but it learned over time (it was rewarded for speed as well as for not hitting other cars).

Neither of us wrote deterministic algorithms for the computer to follow. The program acted randomly at first (literally – we used random.org data) and modified its behavior in response to how good or bad the outcome was. We definitely didn’t include any instructions for computing the velocity or trajectory of an object other than itself.

They are a more sophisticated type of gramophone, playing prerecorded algorithms rather than soundtracks, nothing more.

I guess, broadly speaking, you’re right, but what kind of gramophone behaves randomly? What kind of gramophone changes its own configuration and operation in response to crackling to improve signal-to-noise, without having been taught anything about what kinds of changes would be helpful?

I feel like your idea of a computer is deterministic. I dunno, maybe when you went through undergrad they didn’t encourage neural networking for computer types, so you’re working off an outdated mental model of a computer? I’m a lot younger than you IIRC, that might explain it. (Doesn’t explain your hostility, though.)

Nor did I say anything like what you would have me say, in particular, the part that I have bolded.

C’mon, you’re a math guy. Since when can you refute “A or B or C” on the grounds of not-A? It was/is a more than a little unclear what you meant with that initial statement of yours (below), so Matt took three guesses, increasingly general with each guess, so that C was very nearly a restatement of your claim.

I agree that A is not a super-accurate interpretation of what you said, but it takes quite a bit of effort to understand quite what you mean. Seriously, read what you wrote:

What often gets lost in the noise is that there is nothing stopping a plain old meat bopper from implementing those same algorithms using pencil-and-paper and beating any human who plays chess the old-fashioned way.

The trouble with this statement is that it’s technically true in a rather preposterous way. Nobody has the mental energy to memorize the ten billion or so twelve-piece end game algorithms. Buuuut, perhaps not nobody. Perhaps, I dunno, one person in ten billion can do that. At a rate of completely memorizing one algorithm per second, they could complete the task in about 310 years, so let’s assume that from the age of ten they can memorize ten algorithms per second, with time to practice general chess mastery, so they’re a double-plus-good grand master by 55. Technically, if they managed this, and they could recall each one instantly to mind, then yeah, they could pencil-and-paper it out.

But… it’s preposterous. I’m assuming that you googled and learned that hard-coding the reasonably characterized back-end of the back-end game, there’s billions of end-game states (2^33) with independent algorithms. (I have no idea if this has been implemented, and I might be badly off with that estimate, I didn’t exactly do a rigorous search or thorough read.) A computer can just look it up in a database. Even if you allowed the human lots of books so memorization wasn’t necessary, just storing in mind the organizational system necessary to find the right book would be horrendous and impossible.

Hell, why would they need pencil and paper? If you can recall billions of different procedures to mind, you presumably have the type of mind that could implement each of those billions of algorithms in your head, right? Why allow the person a pencil?

So, ok, I suppose someone could implement chess algorithms, in theory, in the same way that someone could, in theory, be able to state an arbitrarily chosen digit of pi with perfect accuracy. This is kind of abusing the phrase in theory, if you ask me, because to me, and Matt, and most everyone else, it’s totally inconceivable. But okay, whatever, I can’t prove it’s impossible for a super-genius to do, so… you win!

Adding, I remember getting frustrated because the car had figured out that it could just hide in one corner of the screen and not get hit by stuff, and I couldn’t figure out how to teach it that staying still for too long was a bad thing. It had a tendency to exploit faults in my crude programming of what the rectangles would do, like travel at constant velocity in a straight line forever. A friend in the class helped me design (ok, a friend designed) a “vicious” rectangle that would actually hunt down the car (in a crude and deterministic way), and I added some kind of poorly implemented badness measurement for staying fairly still for fairly long. It resulted in kind of erratic and unproductive behavior by the car (probably my fault, I’m not the best programmer). I caught myself feeling a pang of hesitance, conflicted, as if I had somehow traumatized and emotionally scarred a living thing.

Also, for those who are curious about the details, IIRC Gurney’s intro to neural networks book [Amazon link] wasn’t our textbook, but it was on the recommended list on the syllabus and in the library reserves, and I remember enjoying reading it a lot more than our textbook. There’s probably better out there.

I always wanted to write a program with three cars, Cars A and B trying to avoid Car C and each other and Car C trying to hit Car A or Car B, to see what would happen. Like, would the prey cars learn to hide behind each other? When would the hunter car break off from chasing one car to chase the other? … but then that conflicted feeling returns. Take that for what you will.

Salient, thanks for the support, but playing chess by algorithm-by-hand is actually even harder than you have indicated. The problem isn’t needing to memorize a vast table base, although it’s true that the very strongest programs incorporate them. You can still implement strong chess algorithms without large table bases, and the algorithms are within demonstrated human capacity to memorize.

The problem is the sheer number of operations needed to run the algorithm by hand! A modern PC with a strong chess program may execute on the order of 10 billion elementary instructions per second to generate and evaluate on the order of 10 million distinct moves per second. There’s a little wiggle room because a human working by hand may use slightly more complex elementary operations than a modern CPU offers, but not a lot. You’d need many lifetimes to replicate on paper what the computer did in the course of one quick game.

The problem is the sheer number of operations needed to run the algorithm by hand!

Oh, ok, that makes sense. I was hacking together an estimate from a quick search, and probably bundled operation count with independent algorithm count without thinking about it (and come to think of it, I was assuming that each possible collection of pieces remaining on the board would require a different algorithm to execute, which probably isn’t true).

And in those circles – quite standard, I assure you – the question of how fast the machine runs is considered completely irrelevant as to whether or not the machine can be said to think “like a human”.

I feel like we’re just sliding around definitions. Look, I would say my puppy is intelligent. I taught him tricks and games with puppy toys. You can say, naw, that’s not intelligence. I don’t know if it’s “thinking like a human” because the word “like” is doing an awful lot of work there. How would I evaluate whether I am currently “thinking like a human” let alone my puppy? I don’t know what the phrase means.

None of the stuff I’ve said is controversial or obscure, btw.

Seriously, that earlier statement about humans being able to run designed-for-computer chess algorithms and play chess accordingly was super-duper-obscure. And then the part where you said chess is not a timed game? WTF? What game isn’t timed, and how do I sign up, so that I can be immortal and stuff?

And in those circles – quite standard, I assure you – the question of how fast the machine runs is considered completely irrelevant as to whether or not the machine can be said to think “like a human”.

Dude, we’re not trying to figure out if a brain can run like a human [at least, at this point in the conversation and for about the last X hours or so], we’re trying to figure out w.t.f. you meant when you said humans can run chess algorithms on pencil and paper. Or hell, at least that’s what I’ve been trying to figure out, and it sure seems to me that I’m not alone here.

I don’t know what the phrase “think like a human” means. To me, “intelligent” means something like “capable of independently adapting to new input” where “independently” probably just means “without additional strictly deterministic instruction.” So humans surely aren’t the only intelligent beings, by my definition of intelligence. Is there a better definition? I dunno. I’d like to hear it. And I got some intriguing ideas from some of the commenters here about it, which is great! So hey, what’s your definition of intelligence?

where we were talking about the sorts of tasks we could expect these machines to do rather than arguing over whether or not they are doing them in a “human” or “thinking” or “creative” way

Uh, ok. Lots of people were talking about that stuff, e.g. Cian upthread. If that’s what you wanted, you should’ve just started talking about that and given up on the vitriolic condemnation of people who want to talk about creative robots on a bleepin’ science fiction thread. The stuff you said about people playing chess was quite a distraction away from what your stated interest.

ajay@#94: Ok, I’ll embrace the snark. To paraphrase Mencken, “there are two kinds of intelligence. German intelligence and bad intelligence.” Beethoven and Mahler were just the first two, and the earliest, that popped into my head. I could well have singled out Diabate, instead.

dsquared@#97: I’m not all that big on Mozart, but I’m willing to bet that aficionados hearing a meat orchestra performance of one of these pieces would have a reaction along the lines of this was a really off day for Amadeus, he must have phoned it in rather than, oh wow! an undiscovered Mozart masterpiece.

what you’ve got to work with in the physical world is randomness and determinacy.

No, you’ve also got classical (as opposed to quantum) chaos, which is neither random nor deterministic in the normal senses of those words. And it’s the most important factor when you’re dealing with systems built up from 6 or 8 entangled self-organized layers, like the human mind: biomolecules -> organelles (axons, dendrites, etc.) -> neurons -> circuits -> cell layers -> maps -> specialized areas (cerebellum, broca’s region, etc.) -> brain -> nervous system is one way to slice it.

No, you’ve also got classical (as opposed to quantum) chaos, which is neither random nor deterministic in the normal senses of those words.

Nope. Not true. Not for this sort of stuff. Let me quote Scott Aaronson over at Shtetl-Optimised:

An algorithm doesn’t have to be something whose properties we can prove. It doesn’t have to work all the time. It doesn’t have to be “serial” or “deterministic” or “logic-based.” It can be inspired by evolution or any other natural process. Essentially any law-governed process you can possibly imagine can be modeled algorithmically—in other words, simulated by a Turing machine.

In fact, short of doing things like solving the halting problem, essentially the only way the brain could fail to be simulable by a Turing machine would be if it wasn’t governed by physical laws at all.

If rather than sophistically evading this point, the AI critics could show me that they understood it, I’d be much more interested in talking to them.

Note, btw, we had someone up above claim that neural nets didn’t follow an algorithm. It’s this sort of thing that exasperates me, when someone is only half-educated but feels that they are an expert; enough so that they feel obliged to slap anyone down who points out that a) that Just Ain’t So, and b) that this is well-known in the field itself.

In any event, these computationally difficult processes are irrelevant to the question. All you’ve got to work with, I repeat, is determinism and randomness. It’s sort of hard to go from those basic ingredients to what a lot of people apparently mean by “creativity”. Apparently it’s such an ineffable process that it’s impossible to even conceive of it being nothing more than an application of random variation coupled fitness selection rules. Even if they are very . . . complicated :-)