Computation and the Future of the Human Condition
by Stephen Wolfram
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Last annotated on October 25, 2016
Computation and the Future of the Human Condition
I think it’s going to become clear that computation is by far the most important idea that’s emerged in the past century. But in the future I think it’s actually going to become still even more important. Until it’s really the dominant theme of our very nature and existence. Read more at location 19
Well, in my life so far, I’ve basically done three large projects. Read more at location 24
Mathematica in showing me what large-scale formalization can achieve. Read more at location 29
Wolfram|Alpha in helping me understand the span of human knowledge and the automation of a certain kind of intelligence. Read more at location 30
the most important is A New Kind of Science—NKS. Because it provides the paradigm for what I’ll be talking about. Read more at location 32
our experience is that to make something complicated requires having complicated rules, going to lots of effort, and so on. But here when we look out into the computational universe, we’re seeing something completely different, and completely unexpected, going on. Read more at location 74
when one looks at rule 30, or at other cellular automata with simple rules, probably the first thing that comes to mind is stuff one sees in nature. Well, I don’t think that’s a coincidence. Read more at location 87
**** (Note: no good or evil; just existence, it us all "good") When we build things with engineering today, we’re in effect restricting ourselves to particular kinds of programs whose behavior is simple enough to foresee. But nature is under no such constraint. Read more at location 90
In the past, we might have assumed that to get so much more complexity than we usually create with engineering must require something vastly beyond human sophistication—maybe some kind of deity. But nothing superhuman is needed, it’s just little tiny programs in the computational universe. Read more at location 95
if one’s lucky one can then formulate some general principle. Well, in NKS we have such a principle. It’s called the Principle of Computational Equivalence. Read more at location 104
what the principle says is that Read more at location 112
**** after one passes some very low threshold in behavior, every program does computations that are exactly equivalent in their sophistication. Read more at location 117
in the 1930s the big discovery of Alan Turing and so on was that in fact one didn’t need all those different kinds of machines. Instead, one could have a single, universal machine, which could be programmed to do any computation one wanted. Read more at location 120
And today we’re still chasing the idea, building all these sophisticated pieces of technology that are universal computers. But now the Principle of Computational Equivalence tells us something much more extreme. It says we don’t need all that sophisticated technology. Even systems with very simple rules—and simple inputs—can do in a sense arbitrarily sophisticated computations. Read more at location 125
the principle gives us a prediction. It says that we won’t have to go far in the computational universe before we start seeing systems that are computation universal. Well, we can test that prediction. And for several kinds of systems we now know that it’s indeed true. Read more at location 131
Well, to make a prediction, we have to be able to somehow out-compute the system that we’re trying to predict. Well, for systems like idealized planets orbiting a star, that’s always been possible. Read more at location 151
**** In effect, we can computationally reduce the behavior of the system. But will that always be possible? The Principle of Computational Equivalence implies that it won’t. And in fact it implies that even among very simple programs in the computational universe, it’s common to find computational irreducibility. Read more at location 155
The exact sciences have always avoided systems that work like this. But they’re all over the place. Read more at location 161
We’ve always implicitly assumed for our science that we as observers or predictors of systems are much more computationally sophisticated than the systems we’re observing or predicting. But the Principle of Computational Equivalence says that this isn’t true. And that instead we are just equivalent to the systems. Read more at location 163
almost all the technology we have today is created in a very incremental way. We take what has existed historically, and we extend it. Read more at location 179
something, were discovered. And for a while these properties just seemed like curiosities. But eventually it turned out they could be harnessed for things that are incredibly useful for human purposes. And it’s the same story in the computational universe—there are lots and lots of systems out there that do interesting things. But the issue is to match up those behaviors with human purposes. Read more at location 210
Within Mathematica, for example, there are more and more algorithms that weren’t explicitly constructed by humans—but instead were just found by searching the computational universe. Algorithms not only for things like random number generation, but also for function evaluation, data manipulation, image processing, and lots of other things. And Wolfram|Alpha would not have been possible without this kind of approach. Searching for algorithms for linguistic analysis, or data presentation. Read more at location 233
Sometimes the algorithms one finds in the computational universe work in some obviously clever way that one hadn’t thought of. But more often their behavior just looks very complicated—and no more human-understandable than lots of systems in nature. Read more at location 238
One can also emulate biological evolution and natural selection: starting from one system, and then randomly changing it to try to make it better. Read more at location 243
we’ve been very successful in “mining” the computational universe to find useful algorithms. And my guess is that this kind of approach will be a central theme in the future of technology. That it will not be about incremental construction, but rather about searching for useful systems. Read more at location 248
More and more of our technology will just be mined from the computational universe. Known to achieve particular purposes. But not in ways that we as humans can readily understand. In some sense, one might view the current stage of much of our technology as somehow “Galilean”. Operating in a sort of clockwork way, like the Galilean solar system. Read more at location 261
**** individual elements may operate according to simple rules, but the system as a whole shows all sorts of complex behavior. Read more at location 271
**** One important feature of finding things in the computational universe is that some kinds of invention and creativity are automatic, and free. Read more at location 278
There might be a program that we could construct step by step. But by searching the computational universe, we can find a much more efficient program—that will typically happen not to be readily understandable by humans. Read more at location 300
what if you see a splash of paint on a canvas? Is it meaningful, purposeful modern art? Or just a random splash of paint? When we extend these questions about purpose to more abstract settings, we end up asking a lot about meaning. Read more at location 320
******** There’s a certain set of axioms that essentially all the mathematics that’s done today is based on. But they’re certainly not the only possible axioms. Out in the space of all possible axiom systems, there are infinitely many other ones. So why do we pick the particular axiom systems we have for mathematics? Read more at location 324
******* one can do all sorts of analysis, trying to find ways in which the axiom systems we actually use for mathematics are special. Well, I haven’t found any. And it’s not even, for example, that these axiom systems are somehow relevant to the physical universe. They just describe particular corners of it. Read more at location 331
**** what I’ve concluded is that actually the mathematics we have today is really just a historical accident: the direct generalization of the arithmetic and geometry that happened to be used in ancient Babylon. Read more at location 336
is there any criterion we might use to decide abstractly if a thing has a purpose? Read more at location 341
There are two ways we can describe it. One is by its mechanism—just by saying how its rules make it do what it does. But another is by saying that it’s achieving some particular purpose. Well, sometimes it’s a lot easier to describe things in terms of mechanism. But sometimes it may be difficult to describe something in terms of mechanism, but easy to say what purpose it achieves. Read more at location 344
Before we even get to intelligence, let’s talk about the definition of life. Read more at location 382
We can say that there’s a necessary condition for life: that the system exhibits sophisticated computation. But beyond that, there really doesn’t seem to be any kind of abstract definition one can give. The practical definition for us is based on history—and based on the actual historical properties of life on Earth. Read more at location 393
Well, what about intelligence? It’s pretty much the same story. Read more at location 397
**** The only thing that characterizes intelligence is a necessary condition: that a system is capable of sophisticated computation. Read more at location 403
And what the Principle of Computational Equivalence says is that that’s not so silly after all. The fluid dynamics of the weather has just the same computational sophistication—and in a sense mind-like behavior—as a brain. Read more at location 406
A century ago, Marconi was in the middle of the Atlantic on his yacht. And since he was in the radio business, his yacht had a radio mast. And he discovered that even in the middle of the Atlantic he was hearing all this funny whooshing and clicking through his radio. And his first guess was that he was hearing radio signals from the Martians. It seemed like complex, purposeful signals.
...Actually, it was just the physics of the ionosphere.
...Pretty much the same thing happened with pulsars. But now it was the regularity of the pulses that made people think they must be intentional. Read more at location 425
in the end I think one’s just going to realize that there’s no abstract notion of intelligence, extraterrestrial or otherwise. And the thing we’re really talking about when we talk about “intelligence” is human-like intelligence. As for life, intelligence is not something absolute and abstractly definable. It’s something in a sense historical—defined by its connection to a thread of history. Read more at location 452
In the past we were largely limited by what technology we could conceivably reach. In the future, I think we’ll be much more limited by what we choose to consider useful as technology. What will limit us is not the possible evolution of technology, but the evolution of human purposes. Read more at location 468
Let’s imagine that we can make our existence entirely digital—entirely computational. And that we can implement all that computation at the level of individual atoms and electrons and so on. Then all of our existence is defined by the elaborate motions of various atoms and electrons in some lump of material. Read more at location 474
************ (Note: exactly) The Principle of Computational Equivalence tells us that at a fundamental level these processes are no more computationally sophisticated than lots of other processes that happen with atoms and electrons and so on. There’s no abstract computational way to distinguish the lump of material that has us encoded in its behavior from one that’s just an ordinary lump of material, doing its ordinary physics. Read more at location 479
It feels like we just went in a cycle, winding up after all our achievements back as a simple part of nature. Well, in some sense that’s true. But in some sense it’s not. Because even if we can’t make a sharp abstract distinction between us and nature, there is certainly a historical distinction. The lump of material that is our future is tied by a thread of history to our present and past. Read more at location 486
I might say that even though the Principle of Computational Equivalence appears here as a something of downer—telling us we can’t be abstractly special—it tells us something satisfying, too. It tells us that there’s computational irreducibility—and that’s what in a sense makes history, including our history, meaningful. Read more at location 499
*********** computational irreducibility in a sense implies that there is a concrete achievement to that history—one needs to go through all that history to find its outcome. Read more at location 505
When we talk about intelligence, we really right now only have one example of it: human intelligence. Read more at location 509
So in general when we talk about creating artificial intelligence, we’re not talking about achieving some amazing abstract endpoint of computational ability. We’re talking about getting computations set up that are really human-like. That mimic our detailed human features. We don’t want to give our computers their heads; we need to keep them reined in if they’re going to show human-like intelligence. Read more at location 556
********** computational irreducibility is what allows one to go from underlying deterministic rules—even simple rules—to arbitrarily rich, complex, and unpredictable behavior. And among other things, I think it’s at the center of the phenomenon of free will. That there can be a kind of irreducible distance between underlying deterministic laws, and overall observed behavior. So that the overall behavior can appear free of the determinism of the underlying laws. Read more at location 570
suffice it to say that I think there is perfectly good free will in lots of computational systems; it’s certainly not a special human feature. Read more at location 576
Like creativity, for example. One might say, “A computer will never invent anything.” Well, from my point of view, that’s really silly. By mining the computational universe we’ve had computers invent lots and lots of things that we use every day—and Read more at location 580
I’m guessing that if one did a short-piece-of-music Turing test right now, WolframTones would do pretty well relative to the humans. Read more at location 591
There’s a vast space out there of possible things we can harness for technology, and that we can in a sense bring into our lives. But it’s really a question of the evolution of our purposes what we will choose to do that with. Read more at location 601
********* the whole point is that purpose is defined only with respect to a thread—and in effect a sequential thread—of history. Read more at location 624
we only tend to understand the next possible purpose when we get to live within the environment created by the previous one. Read more at location 628
It is interesting to see how the course of history has affected human purposes. Often they have been dominated by religions. And often they have also in effect been dominated by fluctuations: by the emergence, for example, of a particular leader who has defined some purpose that is widely followed. One can think about the space of all possible purposes, and about how different peoples’ purposes and motivations are distributed across that space. There is, as one knows from practical experience, plenty of diversity. Read more at location 637
Perhaps natural selection has had something to do with shaping this diversity. It’s like immunological diversity: a good thing in preventing something bad from affecting too large a fraction of the population. A good way to add robustness. Read more at location 645
There is of course one common feature of humans that defines some aspects of purpose: our mortality—the finiteness of our lives. Read more at location 678
And over the course of our lives, we have to react to all sorts of external stimuli. Well, every so often something goes wrong. Either because of a program bug—a genetic bug. Or because of something to do with a stimulus. That, say, causes a module to blow up, like a driver in an operating system. Well, gradually all kinds of gunk builds up in the state of the operating system. And eventually for one reason or another, it crashes—it dies. Read more at location 683
But I’m afraid computational irreducibility is our big enemy. And ultimately the only way to overcome it will be to have systems that outcompute what is happening to us biologically. Read more at location 702
But I’m somewhat hopeful that there’s in a sense enough computational reducibility in our biological operation that we’ll be able to create systems that outrun it. Read more at location 707
You know, from a really practical point of view, I’m guessing the first dramatic thing that’s going to happen is successful cryonics. It’s a bit like cloning. For years I remember asking people about cloning mammals, and people gave all kinds of arguments about why it couldn’t be done. But then Dolly the sheep arrived—the result of discovering a weird, weird process. Well, I’m strongly guessing it’ll be the same with cryonics. That there’s some weird process that’ll make it just work. It’s a shame more people don’t take that field more seriously. There’s a breakthrough out there to be had. Read more at location 715
We’ve realized that intelligence isn’t nearly as special as we thought; it’s sort of out there all over the universe. But what about something human-like? Read more at location 728
when our current constraints are all removed, our future selves will indeed have a difficult time knowing which of all possible purposes to pursue. But that one of the most important guides will be to look at history. To look back at a time when there were constraints—like mortality and scarce resources—that pruned out possible purposes. Read more at location 761
So from the future, as one tries to analyze history and purposes, one will potentially land right on our times in these years. So that it’ll be our activities and purposes in these years that define the purposes for our whole future. Read more at location 771
I have my next big project picked out: trying to find the fundamental theory of physics. Read more at location 790