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    The Computational Perspective
by   Daniel Dennett

What does computation mean? Daniel Dennett discusses information architecture beyond the mechanized causation in computers and frames the question in terms of the organization of matter itself. What do models of computation tell us about the material world?


Originally published November 19, 2001 at Edge. Published on KurzweilAI.net November 19, 2001.

If you go back 20 years, or if you go back 200 years, 300 years, you see that there was one family of phenomena that people just had no clue about, and those were mental phenomena -- that is, the very idea of thinking, perception, dreaming, sensing. We didn't have any model for how that was done physically at all. Descartes and Leibniz, great scientists in their own right, simply drew a blank when it came to trying to figure these things out. And it's only really with the ideas of computation that we now have some clear and manageable ideas about what could possibly be going on. We don't have the right story yet, but we've got some good ideas. And at least one can now see how the job can be done.

Coming to understand our own understanding, and seeing what kinds of parts it can be made of, is one of the great breakthroughs in the history of human understanding. If you compare it, say, with our understanding of life itself, or reproduction and growth, those were deep and mysterious processes a hundred years ago and forever before that. Now we have a pretty clear idea of how it's possible for things to reproduce, how it's possible for them to grow, to repair themselves, to fuel themselves, to have a metabolism. All of these otherwise stunningly mysterious phenomena are falling into place.

And when you look at them you see that at a very fundamental level they're basically computational. That is to say, there are algorithms for growth, development, and reproduction. The central binding idea of all of these phenomena is that you can put together not billions, but trillions of moving parts and get these entirely novel, emergent, higher-level effects. And the best explanation for what governs those effects is at the level of software, the level of algorithms. If you want to understand how orderly development, growth, and cognition take place, you need to have a high-level understanding of how these billions or trillions of pieces interact with each other.

We never had the tools before to understand what happens when you put a trillion cells together and have them interact. Now we're getting these tools, and even the lowly laptop gives us hints, because we see phenomena happening right on our desks that would just astound Newton or Descartes, or Darwin for that matter, that would look like sheer magic. We know it isn't magic. There's not a thing that's magical about a computer. One of the most brilliant things about a computer is that there's nothing up its sleeve. We know to a moral certainty there are no morphic resonances, psyonic waves, spooky interactions; it's good old push-pull, traditional, material causation. And when you put it together by the trillions, with software, with a program, you get all of this magic that's not really magic.

The idea of computation is a murky idea and it's a mistake to think that we have a clear, unified, unproblematic concept of what counts as computation. Even computer scientists have only a fuzzy grip on what they actually mean by computation; it's one of those things that we recognize when we see it. But it seems to me that probably the idea of computation, itself, is less clearly defined than the idea of matter, or the ideas of energy or time in physics, for instance. The fundamental idea is itself still in some regards a bit murky. But that doesn't mean that we can't have good theories of computation. The question is just where to draw the line that says this is computation, this isn't computation. It's not so clear. Almost any process can be interpreted through the lens of computational ideas, and usually -- not always -- that's a fruitful exercise of reinterpretation. We can see features of the phenomena through that lens that are essentially invisible through any other lens, as far as we know.

Human culture is the environment that we live in. There's the brute physical environment, the streets and the air we breathe, the water we drink, and the cars we travel in, and then there's all the communication going on around us in many different media: everyday conversation, newspapers, books, radios and television, and the Internet. Pigeons live in that world too, but they're simply oblivious to most of it; they don't care what's written in the newspaper that they find their crumbs on. It's immaterial to them what the content, what the information, is. For us it's different; the information is really important.

So if we just think about the informational world that we as a species now live in, we see that, in fact, it's got a lot of structure. It's not amorphous. Everything is not connected to everything else. There are lots of barriers, and there's an architecture to this world of communication. And that architecture is changing very rapidly, and in ways that we don't understand yet.

Let me give you a really simple example of this. You tune in the Super Bowl, and you find that there are these dot-com companies that are pouring an embarrassingly large amount of their initial capitalization into one ad on the Super Bowl; they're trying to get jump-started with this ad. And this is curious so you ask yourself, "If this is an Internet company, why aren't they using the Internet? Why are they doing this retrograde thing of going back and advertising on regular broadcast TV instead of using the Internet?" And the answer, of course, is that there's a fundamental difference in the conceptual architecture of these different media.

When you watch the Super Bowl you are part of a large simultaneous community -- and you know it. You know that you are one of millions, hundreds of millions of people. You're all having the same experience at once, and you know that you are. And it's that second fact, it's that reflexive fact, that's so important. You go to a website, and there might be a hundred million people looking at that website, but you don't know that. You may have read that somewhere but you're not sure, you don't know. The sense that you have when you're communicating on the Web is a much more private sense than when you're watching something on network television. And this has huge ramifications for the credibility conditions. An ad that will work well on television falls flat on the Web, because the people that view it, that read it, that listen to it, don't know what audience they're a part of. They don't know how big a room they are in, whether this is a private communication or a public communication. We don't know yet what kind of fragmentation of the world's audiences is going to be occasioned by the Internet. It brings people together, but it also creates isolation in a way that we haven't begun to assess.

There's a system of what you might call landmarks, and then there's a system of filters. Everybody needs them. That sense of being utterly lost that neophytes have when they first get on the Web -- choosing search engines, knowing what to trust, where home is, whom to believe, what sites to go to is due to the fact that everybody is thirsting for reliable informants or sign posts.

This is something that was established over centuries in the traditional media. You went to the Times and you read it there, and that had a certain authority for you. Or you went to the public library and you read it in the Encyclopedia Britannica. And all of these institutions had their own character, and also their own reputations, and their reputations were shared communally. It was very important that your friends also knew that the Times or the Encyclopedia Britannica was an important place to look. Suppose somebody writes and publishes a volume called "Sammy's Encyclopedia of the World's Information"; it might be the best encyclopedia in the world, but if people in general don't realize it, nobody's going to trust what's in there. It's this credibility issue which, as far as I can see, has not yet even begun to crystalize on the Web. So we're entering uncharted waters there. What comes out of this is very hard to predict. All I know is that we are, indeed, in a period where the whole architecture of our culture is being shifted under our feet, and we don't know where it's going.

We've changed human experience tremendously in the last century and in the last decade. For instance, I'd guess that the average Western-world teenager has heard more professionally played music than Mozart heard in his whole life (not counting his own playing and composing, and rehearsal time!). It used to be that hearing professional musicians in performance was a very special thing. Now not hearing professional musicians is a special thing. There's a soundtrack almost everywhere we go. It's a huge change in the auditory structure of the world we live in. The other arts are similarly positioned. There was a time when just seeing some written words was a pretty big thing. Now of course everything has words on it. People can stand in the shower and read the back of the shampoo bottle. We are completely surrounded by the technology of communication. And that's a new thing. The species, of course, has no adaptations for it, so we're winging it. We're responding to it the best we can.

...Continued at Edge.

Copyright © 2001 by Edge Foundation, Inc.



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credibility and computation
posted on 07/15/2007 7:54 PM by mihai_2

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I agree the web has a huge credibility issue, which is mostly because of the fact that it is a tedious and not always successful process one needs to follow to establish the credibility of a website. This credibility depends on the credibility of the author itself, which was the only step needed to establish credibility in traditional written media.

Human experience has changes as well and even if the 'average Western-world teenager has heard more professionally played music than Mozart' he has also heard much more garbage. This is an issue we face today, yes we value information, however we are bombarded with it and it is not always easy to extract what is useful from all the junk available today.

However if with our current understanding of life, reproduction and growth 'are [essentially] algorithms for growth, development and reproduction' it must be that we are not far from developing those algorithms that will help us decide which information is relevant and which is safe to be ignored. Another supporter of this idea is Kurzweil's law of acceleration returns, by which the power of computation we will have available to us in the near future will be capable of applying algorithms beyond our imagination.