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 Design. Frank Wilczek's Edge Bio Page

Imagine a superintelligent system with far more computational resources than us mere humans that’s trying to make inferences about what the humans who are surrounding it—which it thinks of as cute little pets—are trying to achieve so that it is then able to act in a way that is consistent with what those human beings might want. That system needs to be able to simulate what an agent with greater constraints on its cognitive resources should be doing, and it should be able to make inferences, like the fact that we’re not able to calculate the zeros of the Riemann zeta function or discover a cure for cancer. It doesn’t mean we’re not interested in those things; it’s just a consequence of the cognitive limitations that we have.

As a parent of two small children, a problem that I face all the time is trying to figure out what my kids want—kids who are operating in an entirely different mode of computation, and having to build a kind of internal model of how a toddler’s mind works such that it’s possible to unravel that and work out that there’s a particular motivation for the very strange pattern of actions that they’re taking.

Both from the perspective of understanding human cognition and from the perspective of being able to build AI systems that can understand human cognition, it’s desirable for us to have a better model of how rational agents should act if those rational agents have limited cognitive resources. That’s something I’ve been working on for the last few years. We have an approach to thinking about this that we call resource rationality. And this is closely related to similar ideas that are being proposed in the artificial intelligence literature. One of these ideas is the notion of bounded optimality, proposed by Stuart Russell.

TOM GRIFFITHS is the Henry R. Luce Professor of Information, Technology, Consciousness, and Culture at Princeton University. He is co-author (with Brian Christian) of Algorithms to Live By. Tom Griffiths's Edge Bio Page

It looks as if there’s a general relationship between the very fact of childhood and the fact of intelligence. That might be informative if one of the things that we’re trying to do is create artificial intelligences or understand artificial intelligences. In neuroscience, you see this pattern of development where you start out with this very plastic system with lots of local connection, and then you have a tipping point where that turns into a system that has fewer connections but much stronger, more long-distance connections. It isn’t just a continuous process of development. So, you start out with a system that’s very plastic but not very efficient, and that turns into a system that’s very efficient and not very plastic and flexible.

It’s interesting that that isn’t an architecture that’s typically been used in AI. But it’s an architecture that biology seems to use over and over again to implement intelligent systems. One of the questions you could ask is, how come? Why would you see this relationship? Why would you see this characteristic neural architecture, especially for highly intelligent species?

ALISON GOPNIK is a developmental psychologist at UC Berkeley. Her books include The Philosophical Baby and, most recently, The Gardener and the Carpenter: What the New Science of Child Development Tells Us About the Relationship Between Parents and Children. Alison Gopnik's Edge Bio Page

The questions that I’ve been interested in more recently are about collaboration and what can make it succeed, also about the evolution of disciplines themselves. The part of collaboration that is well understood is that if a team has a diversity of tools and backgrounds available to them—they come from different cultures, they come from different knowledge sets—then that allows them to search a space and come up with solutions more effectively. Diversity is very good for teamwork, but the problem is that there are clearly barriers to people from diverse backgrounds working together. That part of it is not well understood. The way people usually talk about it is that they have to learn each other’s language and each other’s terminology. So, if you talk to somebody from a different field, they’re likely to use a different word for the same concept.

ROBERT AXELROD, Walgreen Professor for the Study of Human Understanding at the University of Michigan, is best known for his interdisciplinary work on the evolution of cooperation. He is author of The Evolution of Cooperation. Robert Axelrod's Edge Bio Page

Part of the definition of intelligence is always this representation model. . . . I’m pushing this idea of distribution—homeostatic surfing on worldly engagements that the body is always not only a part of but enabled by and symbiotic on. Also, the idea of adaptation as not necessarily defined by the consciousness that we like to fetishize. Are there other forms of consciousness? Here’s where the gut-brain axis comes in. Are there forms that we describe as visceral gut feelings that are a form of human consciousness that we’re getting through this immune brain?

CAROLINE A. JONES is a professor of art history in the Department of Architecture at MIT and author, most recently, of The Global Work of Art. Caroline Jones's Edge Bio Page

 I was talking about maps and feelings, and whether the brain is analog or digital. I’ll give you a little bit of what I wrote:

Brains use maps to process information. Information from the retina goes to several areas of the brain where the picture seen by the eye is converted into maps of various kinds. Information from sensory nerves in the skin goes to areas where the information is converted into maps of the body. The brain is full of maps. And a big part of the activity is transferring information from one map to another.

As we know from our own use of maps, mapping from one picture to another can be done either by digital or by analog processing. Because digital cameras are now cheap and film cameras are old fashioned and rapidly becoming obsolete, many people assume that the process of mapping in the brain must be digital. But the brain has been evolving over millions of years and does not follow our ephemeral fashions. A map is in its essence an analog device, using a picture to represent another picture. The imaging in the brain must be done by direct comparison of pictures rather than by translations of pictures into digital form.

FREEMAN DYSON, emeritus professor of physics at the Institute for Advanced Study in Princeton, has worked on nuclear reactors, solid-state physics, ferromagnetism, astrophysics, and biology, looking for problems where elegant mathematics could be usefully applied. His books include Disturbing the Universe, Weapons and Hope, Infinite in All Directions, and Maker of Patterns. Freeman Dyson's Edge Bio Page

I've spent several decades creating a computational language that aims to give a precise symbolic representation for computational thinking, suitable for use by both humans and machines. I'm interested in figuring out what can happen when a substantial fraction of humans can communicate in computational language as well as human language. It's clear that the introduction of both human spoken language and human written language had important effects on the development of civilization. What will now happen (for both humans and AI) when computational language spreads?

STEPHEN WOLFRAM is a scientist, inventor, and the founder and CEO of Wolfram Research. He is the creator of the symbolic computation program Mathematica and its programming language, Wolfram Language, as well as the knowledge engine Wolfram|Alpha. He is also the author of A New Kind of Science. Stephen Wolfram's Edge Bio Page