Jerry Fodor
Monday, November 02, 2009
Discuss 8
'For all of which, the complexity of our minds, or of our behaviour, is simply irrelevant to the question of whether our cognitive architecture evolved under selection pressure. I do think it's remarkable that nobody seems to have noticed this.'
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A blog about, among other things, imaginary ideas - What ifs? and Imagine thats. What if photographs looked nothing like what we see with our eyes? Imagine that the Berlin Wall had never come down. What if we were the punchline of an interminable joke? All contributions welcome.
So, erm, if we are still a long way from understanding how the mind works, or doesn't work, then there's no point holding out much hope that AI will get all that far, at least until we know a lot more. Or so say some. Others are mad for Hal and his pals. Is this the idea behind these discussion points?
ReplyDeleteOne of them, Mark. My primary idea is to get you lot to come up with angles I haven't thought of. Wisdom of Crowds. I know it doesn'r work as such and there's not much of a crowd here, but I'm trying to get it to build somehow.
ReplyDeleteYeah, apart from the wisdom bit and the crowd bit, it's working well.
ReplyDeleteI initially took that statement to be a refutation of blind watchmaker style anti-evolution arguments based on the complexity of our poetry-scribbling, symphony-writing brains; but I suppose it could equally be rebuttal of the whole evolutionary psychology project.
it's the latter, Brit. Brilliantly done too by Fodor. Knocked it down for me
ReplyDeleteWell, I’ll throw in my two pence, not that it’s worth much.
ReplyDeleteThe question of how evolution could have sprung a trick as complicated as the human mind is perhaps parallel to how processors are developing. For a long time, there was the idea that processors would just keep getting bigger and bigger, more complex until they became like the human brain. I’m not sure that Moore’s Law is still holding up but recent processor designs have moved the other way, paradoxically, perhaps becoming more like the brain. Designers have reduced the complexity of the individual elements but make more of them. In Sony’s PS3, there’s the Cell processor which is 7 or 8 cpus. Fiendishly difficult to programme but more powerful when they work. I suppose this concept is behind recent advances: neural networks, bot nets, cloud computing, and even file sharing via Bittorrent. The next big thing will be probably involve some kind of distributed processing.
There’s even a prototype games service called Gaikai being tested where you no longer have a machine in your own home, just streaming the results to your machine. This is probably not the place to mention this but many of the big advances in these areas such as AI are taking place in video gaming.
That, Willard, is JUST the type of contribution I was hoping for, thanks.
ReplyDeleteSo what you're saying Willard, is that lots of simple bits interacting looks more like the human brain (and produces more complexity?) than does a few complex bits?
ReplyDeleteBrit, I'm no expert in this but from what I understand, that's something of the idea behind much of the recent research in processor design.
ReplyDeleteHeat is the big problem for modern processors. They produce too much, too quickly, and can’t get rid of it. You’d have to look into the development of CPUs in the last ten years but I seem to recollect that one of Intel’s problems was that they tried to carry on produced these huge powerhouses of a processor. AMD took the route of simplifying the work but doing more of it. It accounted for their rise. These days, our PCs are becoming more powerful because each generation has more cores (i.e. more parallelism). The actual clock speeds of the processors (which used to be the main way of denoting how fast your PC was P75, P200, P333...) means very little since they’ve not increasing significantly. I think they’re all about 2 to 3 Ghz.
No idea whether this is relevant...
ReplyDeleteHaving decision-making distributed rather than centralised, made piecemeal rather than comprehensive, appears to produce better results in another man-made arena - the modern economy.
Is this something that is common to many (all?) systems- that, to make efficient results more likely than not, a switch from central and complicated to distributed and simple is required once they reach a certain size and complexity?
I found this one of the most interesting quotes so far, without quite knowing what Fodor was on about. I'd like to know more about the debate with Dennett that I now see has been raging. I'm bound to be sympathetic to Jerry, Bryan and Brit on that. But, before that, a word of caution on the silicon and software front.
ReplyDeletePeople have been aware for years that Moore's Law cannot forever deliver smaller, faster, cheaper CPUs to power our Turing (or von Neumann) inspired machines, with the C standing crucially for Central of course. For that reason there's been an enormous amount of research on parallel programming and architectures, for many years, not just recently. Some of the best fruit of that in the real world has to be Google's MapReduce and BigTable, helping to enable the fabulous response times for search we've all got used to from big G. But taken as a whole, parallel programming is proving incredibly difficult, at all kinds of levels. Many algorithms just don't seem to be amenable to being partitioned in a way that makes much difference to their performance. All those 'simpler' processors going to waste, way on into the foreseeable future. And, even more to the point, real world programmers have enough problems with their debugging right now. Parallel programming is exceptionally hard to get right and to test, except in narrow areas. I fully endorse Software Transactional Memory from Simon Peyton-Jones and the Haskell team at Microsoft Research in Cambridge, for example, as I write that - one of the few things that could really help. But still, even with STM and a very pure functional language ... very, very hard.
It needn't affect the philosophical debate of course but the realist combined with the nerd combined with the pedant insisted that I say it.
The wider points about AI I will also leave for now, though it would fair to mark me down as a sceptic on some of that too, much I'm sure to everyone's surprise!
The push for simplification is perhaps cyclic. In the '70s they thought processors would close the gap with high-level programming languages, which was just a daft idea squashed by the RISC revolution in the '80s. The big advantage there was learning to pipeline processors, increasing the internal concurrency.
ReplyDeleteNow the concern is with power--if you can programme n processors to do the task in time then that will probably consume far less energy than running on a single processor running at n times the throughput.
Anyway I think Fodor has an excellent point, and if I have understood Bryan right, I am pleased for the coherence of his project that he has understood it. Complexity is not the issue--its a basic conceptual one.
Not strictly apropos perhaps, but Steve Jones has a two-parter in which I believe he critiques evolutionary psychology, beginning tonight on Radio 4 (9pm).
ReplyDeleteWhat is meant by artificial intelligence? a machine that can replicate the thought processes, decision making processes, is it the intention that this machine will be intellectually superior because it lacks human frailty? It would seem to be an impossible dream.
ReplyDeleteThe present state of the computer processor is a workaround, they have put more hamsters in the wheel, but running side by side and in any case much of the time and effort spent increasing processing capability has been because of the demand for graphics, always more graphics. Willard mentions the application of computer technology in the games industry, does this give us an insight? billions spent on developing the computer to enable it to operate more complex toys? If this is correct what does this teach us about the future application of AI?
Will AI merely be the controller of a new generation of electro-hydraulic-mechanical devices, or is there a more sinister purpose afoot.
Recent history would caution us to beware, remember Oppie in his shed with a fag on and wearing that daft hat.
I'm not sure what is meant by 'artificial intelligence' but I suspect it might have less to do with having true intelligence and more to do with having the appearance of intelligence, in the same way that Wayne Rooney naming his son 'Kai Wayne' will fool some people into thinking it's the sophisticated choice.
ReplyDeleteDoes this mean that the physical evolution of our brains is independent of the environment in which they evolved? i.e. if we all lived in some sort of cave with very little natural variability, would our brains still have the same structure?
ReplyDeleteI would have thought (!) that a simpler world would have led to a simpler brain structure.
I get the feeling I'm missing something (OK, a brain) - perhaps someone could explain it to me?
When Artificial intelligence meets its human counterpart on equal terms will the battle of Megiddo begin.
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ReplyDeleteThis is like Discuss 4 woven together with Discuss 1.
ReplyDeleteI had mentioned that we are probably off the track on our cosmic model. And this discussion is showing how similarly, we are off track when it comes to AI. Our biases are preprogrammed into our computer systems. The great thing, is that if we keep massaging the modules, and keep mixing in enough abduction, and throw in some other biases we come up with, we might come up with a model of how we think. This would lead to theories on how and why we are the way we are, with proponents calling them the best humankind has ever come up with, which would lead into a massive movement for groupthink, similar to what we have in the Dawkins movement today.
In Fodor's statement there is still a bias that psychology has no bearing on the question of evolution--and I read here not the word "question" so much as the word "assumption". It's a cavalier attitude. In the last 100 years, psychology, which used to be the study of the psyche, such as what Freud, Jung, and Assagioli did, became the study of behavior instead. Easy results were not forthcoming, so instead of looking where important information might be hidden, we decided to look only in the light. We decided to redefine psychology as the study of behavior, something which can be objectively observed, measured, and quantified. Fodor's attitude is simply to reassert this historic process of ignoring, or to remain ignorant of what the psyche holds for us. He even throws in complex behavior as being irrelevant. So now if the going gets tough with behavior, we can ignore that as well as ignoring the phenomena of the mental, even the spiritual processes.
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ReplyDeleteI was just reading a poem that made me associate the terms "artificial intelligence" with "fictional character". As soon as we start to objectify who we or someone else might be, we make up an artificial intelligence, a fictional character:
ReplyDeleteFictional Characters ---a poem by Danusha Laméris
How did Fodor measure complexity? On what scale does the complexity of the human brain exceed that of (say) the molecular-level interactions involved in a blade of grass converting sunlight to sugars etc.? Predicting the flight of a foot(soccer)ball when struck by a booted foot(foot), factoring in forces (actionary and reactionary), wind directions, air viscosity etc is hugely complex - way beyond our computational powers I think, even with machinery - but David Beckham does it very well and repeatedly.
ReplyDeleteI think David Beckham refutes hard AI, not sure about Fodor - you'd have to ask David about that.
When Artificial intelligence meets its human counterpart on equal terms will the battle of Megiddo begin.
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Parallel programming is used specifically to serve working software developers, not just computer scientists. It is a complete, highly accessible pattern language that will help any experienced developer "think parallel"-and start writing effective parallel code almost immediately. Instead of formal theory, it deliver proven solutions to the challenges faced by parallel programmers, and pragmatic guidance for using today's parallel APIs in the real world.
ReplyDelete