George Dyson speech: “There’s Plenty of Room at the Top”

Thank you. I’m learning a lot by being here. The title of the sequence of events here is “Living in a Networked World” and I’ve never been anywhere where all the students have Thinkpads. That’s actually a very intriguing thing; right now you’re all just plugging into the wall, but I’m sure if anyone comes back here in five years or six years, all your laptops will be wireless. IBM’s working really hard on that. And then it will actually be the realization of the stuff I talked about in this book: looking back at people who envisioned what will happen when people are really networked together in almost telepathic ways.

I was invited here by the math/computer science department, which is significant that those departments are still together; many places they have split apart. But in the old days the computer department was always in the basement of the math department. My mother worked in various math departments, and the computer guys were always down in the basement; now it’s the other way around. And it was mathematicians who started this. If you look in the index of Darwin Among the Machines, you’ll see, and I counted, that there are 86 mathematicians in the index. All this great stuff that changes the world really came out of the minds of mathematicians.

Myself, I’m not a futurist; I’m a historian. I look back at the past. I believe that as we move onto the future, we tend to forget things that have already been done. Things that were ignored at the time thirty years ago, three hundred years ago are worth looking at again before we move on. So, that’s what I do is look at people who predicted the present. And if they were insightful enough to predict the present, there is some chance that they may have predicted a little ways into the future, and I think that’s better than just going off as people who are futurists do and just make wild predictions that usually are wrong. You cannot predict a branching process; you can only hope that by having some better perspective on the past, you see a little further ahead. And, if you’re in the wilderness and you’re traveling and you don’t want to get lost, you look behind you to see which way you came; if you don’t look back, then you’ll be lost when you try and find your path.

I’m here for the Darwin book, but the real reason I’m here (and I’m not trying to plug this) is this book, which is my kayak book. That was my first book, and that is the hardest thing, to get your first book published. And to encourage those of you who may aspire to something like that, not to give up. This book was rejected by well over twenty publishers. It’s been in print now for fifteen years and is in it’s eighth print, so it wasn’t a bad book. It’s just the nature of publishers to reject things that are not like something that was published last week by somebody else. So, here’s one of my best letters of rejection: “As to the manuscript, I’m afraid it’s not for us and I doubt it could be for any other publisher.” This is from the largest publisher in Canada west of Toronto so it’s a significant publisher, who has looked at the book. It wasn’t that they just disregarded it and sent it back with a pink slip. “It seems to me an eclectic mix of travel log, historical documents, celebration, and even how-to, which falls between all markets without winning any. The economics of color printing would also preclude doing anything so ambitious, but that’s another issue. What the book really needs is a much clearer and tighter editorial concept. I don’t find at all that what you’ve got here makes an essential synthesis, but rather a document which seems unsure of what it wants to achieve. I hope these comments aren’t too severe and that they don’t depress you utterly, but no one is doing you any favor by suggesting that what is here is going to catch some publishers enthusiasm.”

So, there you go. You just have to, when you are rejected, don’t feel rejected. I felt terribly rejected with that book. That book went in the closet for two more years before I showed it to somebody else and finally it did get published. And the publishers choose the title. And, when they chose the title for Darwin among the Machines, they chose the “Evolution of Global Intelligence.” They wanted the “Future of Global Intelligence,” and I insisted, “You can’t do any future, it’s a history book. You just can’t call it future.” But they know that future sells more than history. So it came out as the “Evolution of Global Intelligence,” but it’s really more the other way around. It’s really more about the global intelligence of evolution; the fact that the more we learn as we study evolution, the more we find that evolution is an intelligent process. The more we study ways to really arrive at artificial intelligence or understanding how natural intelligence works, we find that those are evolutionary processes. The two things work both ways.

In Jennifer’s [Burg] discussion group last week, of course, I wasn’t here for it, the question was: ‘Is artificial intelligence possible?’ And, that’s a very good question. We can’t really answer that; it’s sort of the wrong question. One of the reviews of my book that I thought was really the best headline of anything I ever saw, the headline was simply: ‘What if artificial intelligence isn’t?’ And you could take that both ways: ‘What if it’s not intelligent?’ or ‘What if it’s not artificial?’ That actually, artificial intelligence, when we get there, will be something that has evolved by natural processes not by some engineer programming the whole thing. Although, if you go to Microsoft and say that, you will arouse the crowd, who believe that it’s all being programmed. I believe things are happening in a more haphazard way. Then, the question is should we be worried about artificial intelligence? Should we worry that machines are going to replace us and be more intelligent? Obviously, machines are becoming more intelligent; a ThinkPad is more intelligent than a toaster and things are moving ahead, slowly, but they are moving ahead. The question we should be afraid of is, and that’s very important in the context here at Wake Forest, is not whether machines are becoming more intelligent, but the real danger is will people become less intelligent? Because intelligence, part of it is wired in your brain, but most of it is culturally learned. And that’s what education is about, trying to develop the intelligence that your brain is capable of. And that can certainly be reduced. It took millions of years of living very difficult lives and having the human culture and language to develop the intelligence we have and it could very quickly start to atrophy if life becomes too easy for all of us.

I think you’re doing a significant experiment here by computerizing the entire learning process and I was actually very encouraged by what I saw today, some of the things that are on Jennifer’s electronic publication of people doing educational things and they actually looked very small and creative. I think what you want to be afraid of is, for instance, the large textbook publishers, who expect you to buy five hundred dollars worth of textbooks a semester. If they see that you’re not buying those books, they may move in and try to homogenize what you’re getting on your computers. And there are some risks to that, the role of computing becomes more like the role of television. But as it is now, I think you are doing very good things with the machines and using them to enhance the education process rather than replace it with broadcasting. But the broadcasting metaphor is very tempting. And of course we have Time, AOL. This happened in the last week, we have very, very big forces at work to try to move into the internet and possibly turn it into something else.

The question of community security and privacy is a very, very big one. And there are some profound questions facing us, that are going to be on us very soon, which is: are we really going to remain one species, just a human species, or are we going to diverge into different species, which is what genetic engineering opens up to us, the chance for life to diversify in a way it hasn’t diversified except over millions of years, much faster? And then the next question is do we remain of many minds? Now, we all have individual minds or do those minds merge all into one mind? Computers offer that potential. Things can be used for good and for evil and that’s not a reason to stay away from them, it’s just a reason to pay attention. Up until now, we’ve really had situations where we have developed machines that can write information to the mind and we are now able to read information from DNA. As human beings who are concerned about privacy and security, there are really two bodies of information we have in us that are our private information. One is the information we have in our minds and the other is the information in our genes. And, the machine world is moving into that quicker than we are really ready for. The ability to transfer information into our minds at a terrific rate and read the information out of our DNA, all too soon both of those are going to become two way processes, where machines are going to be able to also read information from our minds and write DNA. And we’re just seeing the very beginnings of writing strings of DNA and we’re seeing the very beginnings of machines, many for good. There was something in the paper the other day about truly allowing blind people to see with a direct neuron implant. And that’s the good side, and there also are bad sides.

John Wilkins was a bishop in the seventeenth century and he really addressed that. He wrote an entire book on cryptography, really the first full book on cryptography, which is another case where cryptography can be used by the gangsters or it can be used by the good guys. And he argues that very strongly: “However it will not follow that everything must be suppressed which may be abused. If all those useful inventions that are liable to abuse should therefore be concealed, there is not any art or science which may be lawfully professed.” We have to be careful in just saying, “Cloning is bad and we’re going to stop all research into genetic reengineering, or this or that or something.” Everything has a good side and a bad side and you hopefully learn as a society to make those judgements.

Now, I’ll get to Richard Feynman, who gave what now has become a very famous dinner speech to the annual meeting of the American Physical Society in Pasadena on 29 December, 1959. He proposed building very, very small machines and using small machines to build smaller machines. And at the time that was just Feynman being crazy and ridiculous. He talked about a lot of crazy things. But it actually happened. We did build those small machines and they became microprocessors. There is no way you can build a microprocessor, but you can build a machine that builds a smaller machine, and operates smaller, and finally you reduce this down photographically and you have this tiny machine with millions of transistors on something the size of your fingernail. And he actually got to some of the specifics of evaporating layers of material to make circuits. This is Feynman speaking: “I would like to describe a field in which little has been done, but in which an enormous amount can be done. The principles of physics, as far as I can see, do not speak against the possibility of maneuvering things atom by atom. It’s not an attempt to violate any laws, but it is something that has not been done because we are too big.”

For the same reason that the laws of physics don’t preclude machines becoming very, very small, the laws of physics also do not preclude living things becoming very large. As of now, living things have been limited by the size of their body and nervous system. We get to the size of a dinosaur, that’s about as big as you can get on land; a whale is about as big as you can get in the water, but in theory, you can have organisms that were arbitrarily larger than that; it just hasn’t been done. But it may be done. And what we know of that is that life has the ability to expand and fill whatever niches it finds available and things have opened up now with electromagnetic data transmission and fiber optics and things like that, where it is entirely possible to visualize life extending into a size much larger than it has, but that gets to be science fiction. If you look around you, some of that is starting to happen.

Feynman again: ‘In the year 2000 when you look back at this age they will wonder why it was not until the year 1960 that anyone began seriously to move in this direction.’ And they did move very seriously in that direction. As far as I can tell, the number of microprocessors, or the number of computer chips produced a day now, it’s now 500 million a day of chips. Many of those chips cost less than a dollar each. So, you can say that the average is certainly over hundreds of millions of chips produced every day. The amount of fiber optic cable being spun out is supposedly at, according to Bell Labs, 50,000 miles a day. It’s quite an extraordinary growth of stuff. Memory is down to about a dollar a megabyte. I tried to estimate the size of the entire data storage universe as it exists today and the very rough estimate I get is 300 million terabytes. You can’t really ever grasp that except that it’s more or less equivalent to running a high-speed modem at 30,000 bits per second since the beginning of the known universe 15 billion years ago. So, there’s a huge amount of space of data out there that is all being networked together.

So then Feynman looked at what you could do, what were the physical limits of reading and writing information. And he calculated that all the books in the world which he took as 24 million volumes, assuming 50 to 100 atoms per bit, could be written in this form in a cube of material one two hundredth of an inch wide, so there’s plenty of room at the bottom. Don’t tell me about microfilm.

This fact is of course well known to the biologist who resolved the mystery that existed before we understood how it could be that in the tiniest cell all of the information for the organization of a complex creature such as ourselves can be stored in the form of long chain DNA molecules in which, just as you predicted what the limit would be, about 50 atoms are used for one bit of information. There are two bits of information in every base pair. There are four alternatives, so that’s two bits. What’s interesting is what Fineman proposed: it turns out really that nature got there first. The very small stuff nature is doing very efficiently. Nature is and manipulating and reading and writing information in linear strings that is close to the physical limits of what you can do and is doing it very well. If you look now, if you take the November issue of Science, which I grabbed before I came out here, and you look to the back page, it has classifieds, such as “DNA-Call for prices;” “Special Introductory Price-Custom Gene Synthesis for only $4 a base pair through 12/31/99;” “Custom DNA purified and delivered in 48 hours $1.20 per base.” That must be some basement lab. A dollar twenty per base is $4.80, just under $5, a byte. So that’s the cost today, just if you have a Visa card, that’s the cost for you to read or write the DNA is $4.80 a byte. Then I got out, I have a lot of old computing books, my old 1959 “Data Processing Technology and Economics,” which lists all the statistics at the time. In 1959, and I’m not making this up, the average U.S. price per byte for core memory for a computer, this is random-access memory, was $4.80 a byte. Another revealing figure is the average number of bytes per system, which would be like the big computer a university would have, is one thousand bytes of core memory. So, the cost of reading and writing from DNA right now is exactly the same, not adjusted for inflation, is the same cost of reading and writing out of your main memory of a computer in 1959. And we all know what happened next, after 1959. That price just plummeted to where now $5 gets you five million bytes. Not to make predictions, but that’s my prediction, that we are on the verge of the same degree of revolution if not more so that we were in 1959, when we were on the verge of the computer revolution. We are now on the verge of a biological revolution that is going to be equally dramatic. And I think all of you are going to play a part in it in some way, either having to make choices or actively working on it.

That big bang of the computer universe was really when the first machines were built. The very first machine, that was the archetype of the modern IBM ThinkPads, was a machine that was built in Princeton, right down the hill from where I lived, in a very nondescript brick building. It was started theoretically in 1946. A mathematician by the name of John von Neumann had the idea and he got some other logicians. This was all done by logicians, who at the time (my mother was a logician) were like the most impractical, weirdest people on the planet. What the logicians did was to argue for years about the meaning of truth and things like that. How do you distinguish the difference between something that’s true and something that’s provable? Who cares? And why do this? But those are the guys who created the modern computer. It was done with logic. And then they said, well we can do it with logic, how else could we do it? Leipnitz in the seventeenth century proposed building a binary computer with marbles, running marbles down little tracks with gravity. This is the same as running electrons through a voltage gradiance, exactly the same principle. You could build a computer today using marbles; it just would be the size of New Jersey. They built this thing. They got it running for the first time in 1951. I was born in 1953. And when I started researching the history of the idea of artificial life, the idea that life could inhabit other universes besides our own including the idea that life could grow in a digital universe, I found something quite extraordinary. When I started searching in the archives of this computer project at the Institute for Advance Studies, I found that one of the very first people von Neumann brought there was an Italian-Norwegian mathematician named Nils Baricelli, who came there to do artificial life experiments in 1953. And this was kept rather quiet. I think it was embarrassing, the trustees and so on, I think, had a great fear that, already the press was running things like “Electronic Brain is Being Built in Princeton” and if they said something about artificial life, there could be trouble.

So this stuff was buried for forty years, until I found his papers. He was very explicit. This is his progress report for March 1953, the exact time I was born: “According to the theory of symbiosis of genes, the genes were originally independent, virus-like organisms, which by symbiotic association formed more complex units. A series of numerical experiments are being made with the aim of verifying the possibility of an evolution similar to that of living organisms, taking place in an artificially created universe.” The amazing thing is that he did this work in a very, very small universe, if you take it as a time dependent function. So, if you take the size of the memory and the number of cycles, the institute computer was forty thousand bits, so five thousand bytes, and it was running at a hundred thousand cycles a second. If you compare that to your ThinkPads, running thirty-two megabytes or sixty-four megabytes at three hundred megahertz, sixty million of Barricelli’s universes would fit in one of your ThinkPads. This is the very, very early beginnings. From even those very simple experiments, all done with punch cards input/output, he could see the future of, not to say artificial biology, but just how evolution could happen in a digital medium.

In the logbook, it says this machine ran on vacuum tubes. The memory was stored as dots on the face of cathode-ray tubes. Like when you turn off the television and you have a little image that lasts half a second, it would cycle a potentially small television tube with dots on it hundreds of times a second. Every time it would turn off another output would read the dots so it kept the dot there. That was how they did their memory. You can imagine those things were very sensitive to detectors of magnetic fields or someone walking into the room. The thing was working about a third of the time, and then they got it working about seventy-five percent of the time. But in the logbook for April 1953, the engineer has written: “Dr. Barricelli claims machine is wrong; code is right.” That’s the complaint between the programmers and the engineers. Now, the world has completely switched. In those days, the programs were terribly small. There was no such thing as an operating system, everything was just programmed in absolute addressing, so that programs could be written on a few pages and the program could be completely debugged and be correct. The machine, the hardware, was always failing: vacuum tubes would last a few billion cycles then would go bad. Now it’s completely the reverse; the hardware your machine that’s running at 500 million cycles per second will go all day without having a hardware failure, but the software fails all the time. Now, we have good hardware and bad coding, and then we had good coding and bad hardware. That’s really the problem in modern computing: how to build reliable software that does not crash when it gets to a bad address or something. I think there are ways to do that biology can teach us. And at that time too, programmers were dirt-cheap and memory was terribly expensive. And now it’s exactly the opposite, memory is dirt-cheap and programmers are expensive.

So Barricelli really saw what he was doing clearer than anyone did really until the field of artificial life was supposedly invented by people in Santa Fe, N.M., ten or twenty years ago; it goes back much further. This is him writing in 1954: “From Darwin’s time to this day, somewhat gratuitous optimism has prevailed in many quarters about the possibility of settling that ultimate detail needed for completion of the theory of the nature of living organisms. But a question that might embarrass the optimists is the following: if it is that easy to create living organisms, why don’t you create a few yourself?” And he tried for yearsÖ I met several people who knew Barricelli; he went like a gypsy around to many universities. He was at Vanderbilt for a while. To make his living he was a viral geneticist, but at night between two in the morning and six in the morning he could get computer time. He would run these artificial life things on various people’s computers whenever he could get time. “Something is missing if one wishes to explain the formation of organs and faculties as complex as those of living organisms. No matter how many mutations we make, the numbers will always remain numbers. They will never become living organisms.” That’s his moment of desperation. Later, he learned that what you need is the numbers, they can’t just be numbers, the numbers have to be mapped to doing something. He tried to evolve organisms where the code he was evolving mapped to moves on a chessboard and tried to evolve programs to play chess, way ahead of other people doing thatÖOf course, our sequential coding is mapped toÖamino acids. And amino acids become proteins and then things start happening. And that’s what’s been missing from the digital universe. But in a way, it’s there, because what most software does, if it’s successful, it goes out there and does something. If you wrote an early sub-routine that added two numbers, some of those sub-routines that were written at the institute forty years ago are still running everywhere today. They did something; it was successful. They succeeded. Somebody wrote something called VisiCalc and it became a spreadsheet. So, sort of the phenotype of that is the spreadsheet that we find useful, so it is propagated. And that’s really how evolution has happened in the digital universe.

There are always two sides to everything. If you look at it from our side, it’s just humans and we’re getting better software. If you look at it from the point of view of these numbers in Barricelli’s universe, which at the time there were 5,000 bytes in the entire digital universe, but they were so good at manipulating numbers that they got to work on hydrogen bomb calculations and then they got to work in business. And IBM came in and said, “Oh, this works. Let’s build lots of these machines.” Their world has grown and grown and grown and become more and more successful. Now we have things like a universe so large that Microsoft has the audacity to release something that is 49 million lines of code and you guys will have it on your machines in probably two more years. It’s called Windows 2000. It takes up millions and millions and millions of lines of code.

Barricelli realized the other key thing: that diversity is important. If you have a homogenous universe evolution doesn’t happen. So, he proposed to place the genes in a two-dimensional universe as well as a one-dimensional one. That will make it possible for every species to get in contact with a greater number of organisms and to confront a diversity of situations. In that respect the conditions will be more like those encountered by living organisms on earth. That’s really the significance of the Internet: that the memory that’s just in your computer alone is a very two-dimensional thing. The topology is quite flat and two-dimensional. But when you involve the internet then suddenly it branches out and you have all sort of other dimensions to how code can move around and what the world of the code lives in starts to look a lot different. Then, he started new experiments with separate universes and interchanging the contents of major sectors between three universes. And then he found a lot more evolution happening faster. “The majority of new varieties which have shown the ability to expand are the result of crossing phenomena and not of mutations.” That’s a huge misconception of people. They tend to think that random mutations happen. And in the real world, the real heavy lifting in evolution is not done by mutations; it’s done by recombinations, by taking part of one program and part of another and linking them in a different way. It’s the same way in literature and culture and language and in everything else. That’s what is creativity. Mutations play a part, but it’s not the main key thing. And of course in biology, we call that sex. What Barricelli discovered was that immediately these little analog creatures he was developing found that the successful way to evolve was by crossing over, by, essentially, sexual reproduction. “And if we want to see anything like a body, we must give the genes some material that the organism can eventually use. Given a chance to act on a set of ponds or toy bricks of some sort that numerical organisms will learn how to operate them in a way that increases their chance for survival. And that, of course, is going on in the real world right now. The thing that has come in now so importantly, if you look at what code can operate that really increases its survival, it’s called money. And that essentially has been going on in the digital revolution since the PC revolution. Big Wall Street money has come in and supported things. So if you have successful code, if more money is put into that, then it reinforces itself and grows. And now with the Internet, of course, the whole cycle is moving faster. So the good idea for some new coding can be funded essentially over night. And the evolution is proceeding faster than ever.

So what we have now really, is a complete circle, that is about to be closed and become a larger circle. Life tends to do that, tends to have cycles in it where the genetic code defines a creature that lives its life and then passes on its genes to another creature. And you have this cycle and that’s how evolution works. It started, life as we know it, with these strings of nucleotides, which now, in the way it works, form DNA, which code for amino acids, which become proteins, which then become a creature. That was one loop. Now the computers have become involved and we’re starting to do the genetic engineering. We’re having the electronic world sort of inserting itself into that loop. Computers themselves, now, coding computers is being used to, you can call the sequence into the number in the back of Science magazine with your Visa card. You can get a sequence of DNA that will code for a protein. The big gap right now, everyone thinks that, it’s like reaching for the moon, the project was to decode the entire human genome. And when that project was done, it’s like getting to the moon, that’s the end of the project and we didn’t go further than the moon. The hard part comes later: what do we do with those sequences and how do we understand what proteins they code for and what the proteins do? So that actually, the companies that are doing innovative stuff now have already moved on from the sequence and they’re working on the protein folding and so onÖIn fact IBM, their largest computer, their most powerful machine that they are building now, is directed specifically for that: Interpreting, figuring out how to interpret gene sequences, and to figure out what proteins they will code for. Then, pretty soon, it may be five years, it may be ten years, it may be twenty years, you’re really going to see computer programming that is directly to the biological, living world. That is going to make the evolution of what we know as living things move a whole lot faster. And, the other side of the coin is that it’s going to make evolution of the computing world move much faster.

The question then is intelligence. How do you define intelligence? Where does intelligence come into that? The classic view of AI, artificial intelligence, is that sooner or later somebody is going to build a machine that sits on your desk and can understand our jokes and is obviously intelligent. And I have grave doubts that I will ever live to see that. And I think there may be a dancing paper clip that asks me if I need help printing an envelope. But that’s not artificial intelligence, that’s sort of artificial stupidity. Real intelligence is a much more diffuse, indefinable thing. And I think some of these things that happen with large genetic systems and networks, those have as much intelligence as anything else. And how, just because it doesn’t speak English or operate at our time scale, doesn’t mean it’s not intelligence. And Barricelli was very explicit about that, arguing that we have this very narrow-minded view of intelligence. If it’s not like us it’s not intelligence. “It would be rather unusual to claim that the subject of an intelligence test is unintelligent on the grounds that no intelligence is required to do the job that any single neuron or synapse in its brain is doing. We all agree that no intelligence is required in order to die, when an individual is unable to survive or not reproduce when an individual is unfit to reproduce. But to hold this as an argument against the existence of intelligence behind the achievements in biological evolution may prove to be one of the most spectacular examples of the kind of misunderstandings that may arise before two alien forms of intelligence become aware of one another. That’s one of these prophecies that I think is on the right track. That we are learning that biology has lots of kinds of intelligence that are not our kind of intelligence at all and they operate at different time scales. But they are intelligent; we just have to learn to appreciate different kinds of intelligence.

That sort of precludes the misinterpretation which is that, you know, the classic view is that Darwin sort of destroyed the intelligence of God and made the whole thing into a non-intelligent process, that just pure random chance and natural selection led to the world as it is and that it wasn’t designed by an intelligent being. And that’s true, but it doesn’t necessarily remove intelligence; it just puts the intelligence at a different level. And I think you can also be more open-minded theologically, and say that perhaps that’s the way God works. And maybe it’s not a God who designs from above, but a God who designs from below. And that’s a personal choice to how you look at things, but it’s wrong to say that Darwin was completely removing all intelligence. And Darwin’s most vocal critic was a man named Samuel Butler, who I took the title of my book from. He wroteÖan article in 1863-called “Darwin Among the Machines,” sort of spoofing the Darwinian theory and how that would provide to the world of machines. He was actually quite serious. But he also argued very strongly, and he made enemies with Darwin, which was actually a very big mistake for his career. Here he is arguing in 1887: “The attempt to eliminate intelligence from the main agencies of the universe has broken down. There is design or cunning but it is a cunning not despotically fashioning us from without, as a potter fashions his clay, but inhering democratically within.” So he was saying what I’m sayingÖevolution itself is an intelligent process, and it embodies a larger intelligence than we are.

The same question kind of arises with the question of life. It’s very hard to define intelligence and where does it start and stop, and if you keep breaking it up into little pieces, where do you get? And we have the same problem with life. Butler was very articulate about that too: “The distinction between the organic and inorganic is arbitrary.” That is, it is more coherent with our other ideas and therefore more acceptable to start with every molecule as a living thing and then deduce death as he breaking up of an association or a corporation and to start with inanimate molecules and to smuggle life into them. And when you look at molecular biology today, I’ve been doing a lot of that, it’s uncanny how that it’s sort of looking that wayÖWe find that some of these molecular systems that are way below the level of the cell are amazingly sophisticated and almost acting like living things. Barricelli believed that nucleotides evolved like collective societies of insects who go out and collect amino acids and bring them back to their nest sort of thing. And that’s how they evolve: building collectively, building proteins. And it only much later became an organized society that evolved into DNA as we know itÖIt’s hard to say really, with black and white, where does life start and where does it endÖwhat is non-life and what is life, and the same with intelligence. Maybe, there’s a little bit of intelligence in everything and when you collect a lot of it together, finally you get something that’s obviously intelligence. And then if you have a rock then it’s obviously something completely non-intelligent. But where you can draw the line in between is tough.

The person who first in English was very explicit to articulate that, was Thomas Hobbes, who is sort of the opening character in my book. My book is sort of a collection of heretics who were ahead of their time and said things that people wouldn’t believe and then believed later. But Hobbes, he essentially came very close to being burned at the stake because his ideas angered quite a number of people. And then the king actually pardoned him. Luckily he was a personal friend of the king, so the king kept the authorities from locking him up. So he was writing in 1651, in his great masterpiece Leviathan, where he proposed really the idea that society was a collective organism that had a life of its own. And then people took that, you know I think they misinterpreted a bit. “The question may be put infinitely: how do you know that you know that you know that you know, etc? Therefore we cannot separate thought from thinking matter. It seems rather to follow that a thinking thing is material then it is immaterial.” He is arguing against Descartes who was saying that thought is completely separate from the body. “And so the mind shall be nothing but motions in some parts of an organical body.” That was quite disturbing to many people at the time. Then he got even more explicit about how arithmetic and thought were not necessarily equivalent, but there was something similar there. He was the first to really make that explicit, that just simply from binary arithmetic, addition and subtraction, you can build up step by step all the processes of thought, which is what your ThinkPad that is trying to act more and more intelligent is doing it all just simply by adding ones and zeros. That’s all it knows how to do, is to add zeros and ones and then, by reversing that, subtract zeros and ones. It just knows how to do that 366 million times a second. “By ratiocination I mean computation, how to compute is to collect the sum of many things that are added together or to know what remains when one thing is taken out of another. Ratiocination, therefore, is the same with addition or subtraction, and if any many had multiplication and division, I will not be against it, seeing that multiplication is nothing but addition of equals of one to another and division nothing but a subtraction of equals from one another as often as is possible. So that all ratiocination is comprehended in these two operations of the mind: addition and subtraction.” And that’s essentially what computer programmers do is just take whatever your problem is, if its spreadsheet or a game or whatever, and one layer at a time just reduce it down to adding and subtracting numbers from each other.

Hobbes was also the first person in English I could find that brought up the idea of artificial life. He asked, “Why may we not say that all automata have an artificial life?” And that, again, was a radical thing. Until then, you could be burned by saying life could be created by something besides God. And one of his critics, Alexander Ross, wrote a wonderful essay. You know, in those days, people didn’t argue on the Jerry Springer Show, they wrote little pamphlets against each other. He wrote a pamphlet called “Leviathan Drawn Out with a Hook” that accused Hobbes of claiming that “it was a wind and not a Holy Spirit, which moved upon the waters of creation.” So that essentially was laying the groundwork for the whole Darwinian revolution, a couple hundred years before Darwin, thatÖscience could deal with issues such as creation. And so to be fair to both sides, I’m going to end up here with two quotes, from opposite sides of that, but they really agree. The one is from Charles Darwin, who recognized this very important principle, that organisms are collective societies. An organism is not a monolithic thing; it is whole bunch of millions, or in our case billions, trillions of organisms living all together to create a collective society that becomes a higher organism, until you get down to little tiny things like algae. “An organic being is a microcosm, a little universe foreign to the host of self-propagating organism, inconceivably minute and numerous as the stars.” So Darwin saw that there were levels and the question for us is where does life go next? What are the next levels of life? Because life is never staying at one level, it’s always moved to another.

Then people argue that life doesn’t have any innate drive towards complexity; complexity just sort of happens. And that’s not necessarily true. I think Barricelli with his theories of symbiogenesis had a different view that is probably correct, that symbiosis is an important force, that complex organisms or companies, in the case of Time and Warner and AOL and stuff, there are advantages to merging and becoming larger, and that has become a driving force in evolution, because when you have one company bigger than other companies. That, I think, is why we tend to get rising complexity in biology, and also just because there is empty space there. Life will move to where there’s new ground and if you have something that can find an area where something bigger gets you somewhere new, life will move there. So finally, the origins of life according to the Old Testament, Book of Genesis, “And the evening and the morning were the fifth day.” And that is when the level of creatures we have evolved.

So, that’s the view of evolution in a digital universe in 45 minutes and I’m happy to take questions or hear anything anyone has to say.