Placeholder Image

Subtitles section Play video

  • >>presenter: So, Kevin Kelly is not only one of the foremost innovators and writers about

  • technology, but his personal story is an equally interesting one. He rode his bike across America

  • and back, and wrote a haiku and drew a drawing for every day of that journey. He spent seven

  • years walking across Asia and he published a beautiful book of his photography from his

  • travels, called "Asia Grace." I first met Kevin when I was five or six, when my dad

  • took over the role of editor from him at the Whole Earth Review and Kevin Kelly was a founding

  • executive editor of Wired. He helped design and launch the WELL, the famous, prototypical,

  • virtual community, as well as HotWired, the first commercial web scene. He is one of the

  • founders of the Long Now Foundation and he also creates and publishes the website Cool

  • Tools. He's also a regular contributor to the New York Times magazine, publishing features

  • on digital culture and one of the last ones was an education issue about homeschooling

  • his son and the role that technology played. His books include "Out of Control," "Rules

  • for a New Economy," several editions of the Whole Earth Catalog and today, he's going

  • to be talking his latest book, "What Technology Wants." So, please help me in welcoming Kevin

  • Kelly.

  • [applause]

  • >>Kevin: Thank you, Mimi. That was great. It's great to be back here. About six years

  • ago, I actually gave a talk in thinking about this book, in this very same room on the history

  • and the future of the scientific method. And that talk is now two pages in this larger

  • book, which is about the long term trends in technology. And there's lots of things

  • that I feel I could talk to you about this afternoon, but I think, or I could talk about

  • the future of media, the future of the Internet and the Web and those kinds of things; all

  • of which you probably know a lot more about than I do. And I think I'd rather, instead,

  • like to step back and talk about what technology means and where it, where its place in the

  • world, where it wants to be in our minds as we make all this stuff. So, everyday, you

  • folks are involved in creating new things and the problem is we don't really have a

  • very good theory about what it is that we're making. And so, the current idea about technology

  • is basically one thing after another. All right? We produce one thing after another

  • and there's no larger framework about whether these are good things, whether we want more

  • of it, where it fits into the cosmos, how it relates to nature and what I'm trying to

  • do is basically, make a first draft for a theory of technology; so you can think of

  • it in those terms. And so, that sounds kind of really esoteric, but here's a definition

  • that most people think about what technology is, is about anything that was invented after

  • you were born; it's all this new stuff, the stuff that's coming out of labs here. And

  • if you're maybe a little more sophisticated, you might think of it as stuff that doesn't

  • work yet and, or maybe it's the stuff that's in your pockets. Or maybe anything that has

  • an on or off switch. And, I think, of course, all those gadgets and all those things are

  • the stuff that technology is, but it's actually something more than that. We can take two

  • pictures, these two artifacts that are approximately the same size and shape and one of them can

  • easily be made by any of us here--not maybe as well-- and that's the tool of the hammer

  • and that's prehistoric. Or the one on the right, the mouse or the iPhone or whatever

  • you wanna look at, that one not only could not any of us do, but even the group of us

  • here could not do. And, in fact, even everyone in this building could not actually produce

  • that. And that's because that device requires maybe a thousand intermediate technologies

  • to create it and maintain it and operate it, and each of those technologies might, in turn,

  • depend on another hundred intermediate technologies. So, what we have is the technology we have,

  • like on the right, is actually representative of an ecology of technologies. It's a whole

  • set of interrelated, interdependent and codependent artifacts and that that entire ecology, or

  • if you can like, if you wanna think of it as a super organism of technology, is actually

  • what I'm most interested in. And to distinguish that from the individual technologies or artifacts;

  • I call that the "technium." So, the technium is this huge, super hive, super ecology of

  • all the technologies that we have as they are related to each other and codependent

  • on each other. And what we know about systems, that have that degree of complexity, there's

  • two things. The one thing that we know about those kinds of systems is that, first of all,

  • they exhibit behaviors that are not present in any of the parts, ok? So, you can look

  • forever into a tin-, into a bee or an ant and you'll never see the hive or the colony.

  • So, that behavior is not present in the individual components. And so, the pres-, the actual

  • behavior, the technium, is not present in any of the devices; it has a larger system-wide

  • behavior. And secondly, those behaviors have inherent biases and tendencies. That's what

  • we know about systems, ok? And the more recursive circuits there are in this, the more tendencies

  • there are, and so, recursive circuit is the idea here, the infinite loop or recursive

  • loop, where we see this in biology. We have genes. A lot of the genes in our chromosomes

  • are turning on other genes; they're not expressing protein, but they're turning on other genes

  • and some of those genes are turning on other genes, and some of those genes are turning

  • on the first genes. And so, you have this recursive loop. We have technologies that

  • make; technology A makes technology B, technology B makes C, and C is involved in the creation

  • of A, so we have recursive loops within the technium and whenever you have those, you

  • have biases, tendencies. And so, when I talk about what technology wants, what I'm talking

  • about is what the technium is biased towards. So, it's, I don't mean "want" in terms of

  • the way in which an intelligence or conscious being would want, but I mean "want" in the

  • way that plants want light. They're leaning towards light. The tomato plant on your windowsill's

  • leaning towards the light; it's not conscious, it's not intelligent. It has a bias in its

  • system, an urge and need, to move towards light. And so, we have plants that want light

  • and that is what the technium has, is certain wants. And the question I'm asking is, in

  • general, what are the biases in the technium? And I begin, if, going back to plants, because

  • my premise is that, in fact, the technium is an extension coming from us. It's not just

  • from our minds, it's also from a biological past; from our evolutionary past, that the

  • technium is actually extending and accelerating those same forces. And so, I ask what does

  • evolution want? Now, I have to say right away is that there are some evolutionary biologists.

  • Among the most prominent was the late Stephen Jay Gould, who argued very, very forcefully

  • that there are no trends in evolution at all; that it's trendless. That there's no trajectories,

  • there's no directions. And that is the orthodoxy in evolutionary biology right now, but there

  • is, there are minority view and there are other evolutionary biologists and many of

  • them young, who actually have more experience with computational and computer simulations,

  • who actually make a different argument and have evidence to show that there are trends,

  • directions, in the long course of evolution. And, and the foremost of those is the ones

  • that we all intuitively feel, which is that over 3.7 billion years of life that life has

  • gotten more complex. Now, the reason why that's maybe not an obvious trend is, Stephen Jay

  • Gould would say, "Well, if you're starting off simple, you have nowhere else to go but

  • more complex." And so, the fact that the leading edge is getting more complex is trivial; it's

  • not important. The question is about the trailing edge. And so, we can show, in fact, that when

  • you have moved along some evolution and you are somewhat complex, is there any bias in

  • which direction you go then? And we can show that there's a mild drift towards increasing

  • complexity, even at the trailing edge of evolution; say bacterium. So, what does evolution want?

  • Well, again, there is a trend. We have evidence that there is a trend in greater complexity

  • over 3.7 billion years of life; that's one trend. But there's also trends towards more

  • diversity; increasing numbers of different species. And again, that increasing diversity

  • happens not just when you're starting off with simple, but even wants to have some diversity;

  • it rarely goes to less diverse. It generally, on average, goes to more diverse. And we can

  • actually make a list of these things including increasing complexity, increasing diversity,

  • increasing specialization. The first cells are general. There's one kind of cell that

  • does everything. Over time, they evolve into specialties and so we have 250 different cell

  • types in our bodies. We can show the number of cell types increases over time in evolutionary

  • history. Increasing mutualism, codependency on other organisms as for your life, increasing

  • ubiquity, increasing mindfulness, sentience. We see the mind and the kind of learning that

  • a brain does and neurons, even happens in plants. We see it erupting throughout the

  • kingdom of life many, many times independently. There's increasing learning and evolvability,

  • which is the ability to evolve and so we forget the fact that the evolution process itself,

  • is not a singular, fixed process, but itself has evolved in complexity and it actually

  • has made things easier to evolve over time. So, it's actually, organisms can evolve faster,

  • quicker and more degrees of freedom now than they could two billion years ago. So, there

  • is actually the evolution of evolvability over time. And exotropy, which is increasing

  • order, increasing self-organization and increasing structure. So, those are the kinds of things

  • that we see and the reason why that's important is because, I think, one of the most amazing

  • discoveries in the last 50 years has been the realization that the essence of life was

  • not water or some vital spirit or some mystical force in the world, but actually was information.

  • We saw that with the discovery of the DNA code; we can understand that the essence of

  • life was actually information processing. And, of course, that's the essence of technology

  • and it wasn't too long ago, for the first time, that we actually exported Darwinian

  • evolution and moved it in to a computational world and they, for instance, we used it to

  • evolve computer code. Microsoft Word has parts of its code that was evolved and not actually

  • programmed by humans. So, we moved evolution out of biology into computers and at the same

  • time, we could take E. coli and assign numbers to its genetic sequences and in parallel,

  • as a proof of concept, used it as a parallel processing machine to solve a travelling salesman

  • program. So, we used the parallel processing of E. coli genetics to solve a computer program.

  • So, we have evolution moving in computers; we have life and evolution moving from life

  • and doing computation, showing that in some senses, that there's equivalency between life

  • and the technium--that the division that we normally think of them, as a gulf, is not

  • there. In fact, there is a continuum between the two. So, that means that when we look

  • at things like this, this 17, 1800s, this diversity of smoke catchers is almost like

  • a museum collection of different species of butterflies and we see specialization, of

  • course, happening in the technium in mechanical things. We make a computer or a camera, and

  • then we might make this specialized underwater camera and infrared camera and a high-speed

  • camera and then we can specialize that to make a specialized infrared camera, and then

  • a specialized infrared underwater camera and so it goes on and on; that specialization

  • is happening. And we can even map, in some cases, the genealogy of different inventions.

  • And I think that's, the parallels are so steep that, in fact, we might even think of, these

  • are the six kingdoms of life: plants, animals, fungi and three kinds of bacteria. We might

  • think of these six kingdoms of life as actually producing the seventh kingdom, and I think

  • of the technium as basically the seventh kingdom of life because it shares so many of the attributes

  • as a system, again, as a technium; not the individual artifacts, but as a system, it

  • exhibits so many of the same self-organizing forces that life does that we, that I think

  • of it as the seventh kingdom of life. So, when I ask what does technology want, what

  • are the biases and the long-term trends in technology, I get a very similar answer. And

  • again, I wanna go back to the idea that "want" is not conscious, but is real that even unintelligent

  • systems can have wants. So, this is the Willow Garage PD2, I think, robot which has been

  • programmed to find its own energy; to recharge itself. And so, it will roam through its building

  • looking for outlets and then takes its tail plug and it plugs in by itself, it plugs into

  • the outlet until its recharged and then it takes off again. And I had the privilege of

  • standing between it and the outlet and it very definitely wanted energy. You could feel

  • it. And it was gonna find it somehow or another and it was not conscious, it was not aware,

  • it was not very intelligent, but it definitely wanted electricity. And so, if we again ask

  • what the technium wants, what it wants is the same thing. It wants to head towards;

  • it's a general bias to drift towards increasing complexity, increasing diversity, increasing

  • specialization, increasing mutualism, ubiquity, sentience and evolvability, among other things.