Special Events

Is Superintelligence Impossible?

On Possible Minds: Philosophy and AI with Daniel C. Dennett and David Chalmers
[4.10.19]

[ED. NOTE: On Saturday, March 9th, more than 1200 people jammed into Pioneer Works in Red Hook, Brooklyn, for a conversation between two of our greatest philosophers, David Chalmers and Daniel C. Dennett:  "Is Superintelligence Impossible?" the next event in Edge's ongoing "Possible Minds Project." Watch the video, listen to the EdgeCast, read the transcript. Thanks  to  physicist, artist, author, and Edgie Janna LevinDirector of Sciences at Pioneer Works, who presented the event with the support of Science Sandbox, a Simons Foundation initiative. —JB]


Reality Club Discussion: Andy Clark


Somebody said that the philosopher is the one who says, "We know it’s possible in practice, we’re trying to figure out if it’s possible in principle." Unfortunately, philosophers sometimes spend too much time worrying about logical possibilities that are importantly negligible in every other regard. So, let me go on the record as saying, yes, I think that conscious AI is possible because, after all, what are we? We’re conscious. We’re robots made of robots made of robots. We’re actual. In principle, you could make us out of other materials. Some of your best friends in the future could be robots. Possible in principle, absolutely no secret ingredients, but we’re not going to see it. We’re not going to see it for various reasons. One is, if you want a conscious agent, we’ve got plenty of them around and they’re quite wonderful, whereas the ones that we would make would be not so wonderful. —Daniel C. Dennett

One of our questions here is, is superintelligence possible or impossible? I’m on the side of possible. I like the possible, which is one reason I like John’s theme, "Possible Minds." That’s a wonderful theme for thinking about intelligence, both natural and artificial, and consciousness, both natural and artificial. … The space of possible minds is absolutely vast—all the minds there ever have been, will be, or could be. Starting with the actual minds, I guess there have been a hundred billion or so humans with minds of their own. Some pretty amazing minds have been in there. Confucius, Isaac Newton, Jane Austen, Pablo Picasso, Martin Luther King, on it goes. But still, those hundred billion minds put together are just the tiniest corner of this space of possible minds. —David Chalmers

David Chalmers is University Professor of Philosophy and Neural Science and co-director of the Center for Mind, Brain, and Consciousness at New York University. He is best known for his work on consciousness, including his formulation of the “hard problem” of consciousness;  Daniel C. Dennett is University Professor and Austin B. Fletcher Professor of Philosophy and director of the Center for Cognitive Studies at Tufts University. He is the author of a dozen books, including Consciousness Explained, and, most recently, From Bacteria to Bach and Back: The Evolution of Minds;  John Brockman, moderator, is a cultural impresario whose career has encompassed the avant-garde art world, science, books, software, and the Internet. He is the author of By The Late John Brockman and The Third Culture; editor of the Edge Annual Question book series, and Possible Minds: 25 Ways of Looking at AI.

 

The Overdue Debate


Front Page

DEFGH Nr. 63, Freitag, 15. März 2019. 

Collage: Stefan Dimitrov

The Ghost in the Machine
Artificial intelligence inspires wild fantasies, but remains hard to imagine. A SZ series creates clarity. 

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Artificial intelligence:
A new series brings science and culture together to fathom the inexplicable

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Possible Minds

25 Ways of Looking at AI
[1.30.19]

Brockman and Minksy by Jean Pigozzi
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rockman and Minsky, 1985       (enlarge      (Photo: Jean Pigozzi)

"Intelligences born and intelligences made have a lot to offer each other. For that beneficial blend to occur, the contextual framing that the voices in this book spell out will be crucial." 
—Stewart Brand

"While the [Possible Minds] authors disagree on the answers, they agree on the major question: what dangers might AI present to humankind? Within that framework, the essays offer a host of novel ideas. . . . Enlightening, entertaining, and exciting reading."—Publishers Weekly

"Pithy essays on artificial intelligence. . . . Readers . . . will not find a better introduction than this book."—Kirkus 

"Brockman, founder of the online salon Edge.org, corrals 25 big brains—ranging from Nobel Prize-winning physicist Frank Wilczek to roboticist extraordinaire Rodney Brooks—to opine on this exhilarating, terrifying future."
Inc. ("10 Business Books You Need to Read in 2019")



Emergences

[9.4.19]

My perspective is closest to George Dyson's. I liked his introducing himself as being interested in intelligence in the wild. I will copy George in that. That is what I’m interested in, too, but it’s with a perspective that makes it all in the wild. My interest in AI comes from a broader interest in a much more interesting question to which I have no answers (and can barely articulate the question): How do lots of simple things interacting emerge into something more complicated? Then how does that create the next system out of which that happens, and so on?

Consider the phenomenon, for instance, of chemicals organizing themselves into life, or single-cell organisms organizing themselves into multi-cellular organisms, or individual people organizing themselves into a society with language and things like that—I suspect that there’s more of that organization to happen. The AI that I’m interested in is a higher level of that and, like George, I suspect that not only will it happen, but it probably already is happening, and we’re going to have a lot of trouble perceiving it as it happens. We have trouble perceiving it because of this notion, which Ian McEwan so beautifully described, of the Golem being such a compelling idea that we get distracted by it, and we imagine it to be like that. That blinds us to being able to see it as it really is emerging. Not that I think such things are impossible, but I don’t think those are going to be the first to emerge.

There's a pattern in all of those emergences, which is that they start out as analog systems of interaction, and then somehow—chemicals have chains of circular pathways that metabolize stuff from the outside world and turn into circular pathways that are metabolizing—what always happens going up to the next level is those analog systems invent a digital system, like DNA, where they start to abstract out the information processing. So, they put the information processing in a separate system of its own. From then on, the interesting story becomes the story in the information processing. The complexity happens more in the information processing system. That certainly happens again with multi-cellular organisms. The information processing system is neurons, and they eventually go from just a bunch of cells to having this special information processing system, and that’s where the action is in the brains and behavior. It drags along and makes much more complicated bodies much more interesting once you have behavior.

W. DANIEL HILLIS is an inventor, entrepreneur, and computer scientist, Judge Widney Professor of Engineering and Medicine at USC, and author of The Pattern on the Stone: The Simple Ideas That Make Computers Work. W. Daniel Hillis's Edge Bio Page

[ED. NOTE:] As a follow-up to the completion of the book Possible Minds: 25 Ways of Looking at AI, we are continuing the conversation as the “Possible Minds Project.” The first meeting was at Winvian Farm in Morris, CT. Over the next few months we are rolling out the fifteen talks—videos, EdgeCasts, transcripts.

From left: W. Daniel HillisNeil GershenfeldFrank WilczekDavid ChalmersRobert AxelrodTom GriffithsCaroline JonesPeter GalisonAlison GopnikJohn BrockmanGeorge DysonFreeman DysonSeth LloydRod BrooksStephen WolframIan McEwan. Project participants in absentia: George M. ChurchDaniel KahnemanAlex "Sandy" PentlandVenki RamakrishnanAndy Clark. (Click to expand photo)

Epistemic Virtues

[8.21.19]

I’m interested in the question of epistemic virtues, their diversity, and the epistemic fears that they’re designed to address. By epistemic I mean how we gain and secure knowledge. What I’d like to do here is talk about what we might be afraid of, where our knowledge might go astray, and what aspects of our fears about how what might misfire can be addressed by particular strategies, and then to see how that’s changed quite radically over time.

~~

James Clerk Maxwell, just by way of background, had done these very mechanical representations of electromagnetism—gears and ball bearings, and strings and rubber bands. He loved doing that. He’s also the author of the most abstract treatise on electricity and magnetism, which used the least action principle and doesn’t go by the pictorial, sensorial path at all. In this very short essay, he wrote, "Some people gain their understanding of the world by symbols and mathematics. Others gain their understanding by pure geometry and space. There are some others that find an acceleration in the muscular effort that is brought to them in understanding, in feeling the force of objects moving through the world. What they want are words of power that stir their souls like the memory of childhood. For the sake of persons of these different types, whether they want the paleness and tenuity of mathematical symbolism, or they want the robust aspects of this muscular engagement, we should present all of these ways. It’s the combination of them that give us our best access to truth." 

PETER GALISON is a science historian; Joseph Pellegrino University Professor and co-founder of the Black Hole Initiative at Harvard University; and author of Einstein's Clocks and Poincaré’s Maps: Empires of Time. Peter Galison's Edge Bio Page

AI That Evolves in the Wild

[8.14.19]

I’m interested not in domesticated AI—the stuff that people are trying to sell. I'm interested in wild AI—AI that evolves in the wild. I’m a naturalist, so that’s the interesting thing to me. Thirty-four years ago there was a meeting just like this in which Stanislaw Ulam said to everybody in the room—they’re all mathematicians—"What makes you so sure that mathematical logic corresponds to the way we think?" It’s a higher-level symptom. It’s not how the brain works. All those guys knew fully well that the brain was not fundamentally logical.

We’re in a transition similar to the first Macy Conferences. The Teleological Society, which became the Cybernetics Group, started in 1943 at a time of transition, when the world was full of analog electronics at the end of World War II. We had built all these vacuum tubes and suddenly there was free time to do something with them, so we decided to make digital computers. And we had the digital revolution. We’re now at exactly the same tipping point in history where we have all this digital equipment, all these machines. Most of the time they’re doing nothing except waiting for the next single instruction. The funny thing is, now it’s happening without people intentionally. There we had a very deliberate group of people who said, "Let’s build digital machines." Now, I believe we are building analog computers in a very big way, but nobody’s organizing it; it’s just happening.

GEORGE DYSON is a historian of science and technology and author of Darwin Among the Machines and Turing’s Cathedral. George Dyson's Edge Bio Page

The Language of Mind

[8.8.19]

Will every possible intelligent system somehow experience itself or model itself as having a mind? Is the language of mind going to be inevitable in an AI system that has some kind of model of itself? If you’ve just got an AI system that's modeling the world and not bringing itself into the equation, then it may need the language of mind to talk about other people if it wants to model them and model itself from the third-person perspective. If we’re working towards artificial general intelligence, it's natural to have AIs with models of themselves, particularly with introspective self-models, where they can know what’s going on in some sense from the first-person perspective.

Say you do something that negatively affects an AI, something that in an ordinary human would correspond to damage and pain. Your AI is going to say, "Please don’t do that. That’s very bad." Introspectively, it’s a model that recognizes someone has caused one of those states it calls pain. Is it going to be an inevitable consequence of introspective self-models in AI that they start to model themselves as having something like consciousness? My own suspicion is that there's something about the mechanisms of self-modeling and introspection that are going to naturally lead to these intuitions, where an AI will model itself as being conscious. The next step is whether an AI of this kind is going to naturally experience consciousness as somehow puzzling, as something that potentially is hard to square with basic underlying mechanisms and hard to explain.

DAVID CHALMERS is University Professor of Philosophy and Neural Science and co-director of the Center for Mind, Brain, and Consciousness at New York University. He is best known for his work on consciousness, including his formulation of the "hard problem" of consciousness. David Chalmers's Edge Bio Page

Morphogenesis for the Design of Design

[7.31.19]

As we work on the self-reproducing assembler, and writing software that looks like hardware that respects geometry, they meet in morphogenesis. This is the thing I’m most excited about right now: the design of design. Your genome doesn’t store anywhere that you have five fingers. It stores a developmental program, and when you run it, you get five fingers. It’s one of the oldest parts of the genome. Hox genes are an example. It’s essentially the only part of the genome where the spatial order matters. It gets read off as a program, and the program never represents the physical thing it’s constructing. The morphogenes are a program that specifies morphogens that do things like climb gradients and symmetry break; it never represents the thing it’s constructing, but the morphogens then following the morphogenes give rise to you.

What’s going on in morphogenesis, in part, is compression. A billion bases can specify a trillion cells, but the more interesting thing that’s going on is almost anything you perturb in the genome is either inconsequential or fatal. The morphogenes are a curated search space where rearranging them is interesting—you go from gills to wings to flippers. The heart of success in machine learning, however you represent it, is function representation. The real progress in machine learning is learning representation. How you search hasn’t changed all that much, but how you represent search has. These morphogenes are a beautiful way to represent design. Technology today doesn’t do it. Technology today generally doesn’t distinguish genotype and phenotype in the sense that you explicitly represent what you’re designing. In morphogenesis, you never represent the thing you’re designing; it's done in a beautifully abstract way. For these self-reproducing assemblers, what we’re building is morphogenesis for the design of design. Rather than a combinatorial search over billions of degrees of freedom, you search over these developmental programs. This is one of the core research questions we’re looking at.

NEIL GERSHENFELD is the director of MIT’s Center for Bits and Atoms; founder of the global fab lab network; the author of FAB; and co-author (with Alan Gershenfeld & Joel Cutcher-Gershenfeld) of Designing Reality. Neil Gershenfeld's Edge Bio Page

Ecology of Intelligence

[7.23.19]

I don't think a singularity is imminent, although there has been quite a bit of talk about it. I don't think the prospect of artificial intelligence outstripping human intelligence is imminent because the engineering substrate just isn’t there, and I don't see the immediate prospects of getting there. I haven’t said much about quantum computing, other people will, but if you’re waiting for quantum computing to create a singularity, you’re misguided. That crossover, fortunately, will take decades, if not centuries.

There’s this tremendous drive for intelligence, but there will be a long period of coexistence in which there will be an ecology of intelligence. Humans will become enhanced in different ways and relatively trivial ways with smartphones and access to the Internet, but also the integration will become more intimate as time goes on. Younger people who interact with these devices from childhood will be cyborgs from the very beginning. They will think in different ways than current adults do.

FRANK WILCZEK is the Herman Feshbach Professor of Physics at MIT, recipient of the 2004 Nobel Prize in physics, and author of A Beautiful Question: Finding Nature’s Deep DesignFrank Wilczek's Edge Bio Page

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