Sunday, January 15, 2012


It's that time of year again . . . the time when Edge poses a single question to great thinkers from a variety of fields and shares their answers with us. This year's question is . . . .


Here is the post from Edge.
— John Naughton, The Observer 

Scientists' greatest pleasure comes from theories that derive the solution to some deep puzzle from a small set of simple principles in a surprising way. These explanations are called "beautiful" or "elegant". Historical examples are Kepler's explanation of complex planetary motions as simple ellipses, Bohr's explanation of the periodic table of the elements in terms of electron shells, and Watson and Crick's double helix. Einstein famously said that he did not need experimental confirmation of his general theory of relativity because it "was so beautiful it had to be true."


Since this question is about explanation, answers may embrace scientific thinking in the broadest sense: as the most reliable way of gaining knowledge about anything, including other fields of inquiry such as philosophy, mathematics, economics, history, political theory, literary theory, or the human spirit. The only requirement is that some simple and non-obvious idea explain some diverse and complicated set of phenomena. [Thanks to Steven Pinker for suggesting this year's Edge Question and to Stewart Brand, Kevin Kelly, and George Dyson for their ongoing advice and support.]

188 CONTRIBUTORS (126,700 words): Emanuel Derman, Nicholas Humphrey, Dylan Evans, Howard Gardner, Jeremy Berstein, Rudy Rucker, Michael Shermer, Nicholas Carr, Susam Blackmore, Scott Atran, David Christian, Andy Clark, Donald Hoffman, Derek Lowe, Roger Schank, Arnold Trehub, Timothy Taylor, Cliff Pickover, Ed Regis, Jared Diamond, Robert Provine, Richard Nisbett, Peter Woit, Haim Harari, Satyajit Das, Juan Enriquez, Jamshed Bharucha, Richard Foreman, Scott D. Sampson, Jonathan Gotschall, Keith Devlin, Clay Shirky, Steven Pinker, Gloria Origgi, Sean Carroll, Irene Pepperberg, Tor Nørretranders, Alan Alda, Jennifer Jacquet, George Dyson, Nigel Goldenfeld, Aubrey De Grey, Nassim Nicholas Taleb, George Church, Kevin Kelly, Stephen M. Kosslyn and Robin S. Rosenberg, Lawrence M. Krauss, James Croak, Armand Marie Leroi, Leonard Susskind, Douglas Rushkoff, Victoria Stodden, Daniel C. Dennett, Shing-tung Yau, Philip Campbell, Freeman Dyson, Mihaly Csikszentmihalyi, Martin Rees, Stanislas Dehaene, Samuel Arbesman, David Gelernter, Timothy D. Wilson, Judith Rich Harris, Samuel Barondes, Peter Atkins, Robert Kurzban, Todd C. Sacktor, Gerald Holton, Frank Wilczek,  Elizabeth Dunn, Eric J. Topol, Lee Smolin, Roger Highfield, Michael I. Norton, Richard Dawkins, Carl Zimmer, Neil Gershenfeld, Alison Gopnik, Terrence J. Sejnowski, Rodney Brooks, Philip Zimbardo, Nicholas A. Christakis, Marcel Kinsbourne, Thomas A. Bass, Randolph Nesse, Sherry Turkle, Gino Segre, Eric R. Kandel, Hugo Mercier, Beatrice Golomb, Benjamin Bergen, Alun Anderson, Alvy Ray Smith, Katinka Matson, Steve Giddings, Hans Ulrich Obrist, Gerd Gigerenzer , Gerald Smallberg, Paul Steinhardt, Adam Alter, Karl Sabbagh, David G. Myers, Lica DiBiase, Stuart Pimm, James J. O'Donnell, Albert-László Barabási, Simon Baron-Cohen, Charles Seife, Patrick Bateson, Carlo Rovelli, Jordan Pollack, Robert Sapolsky, Frank Tipler, Bruce Parker, Marcelo Gleiser, Gary Klein, Ernst Pöppel, Evgeny Morozov, Gregory Benford, S. Abbas Raza, Rebecca Newberger Goldstein, Thomas Metzinger, David Haig, Melanie Swan, Laurence C. Smith, John C. Mather, Seth Lloyd, P. Murali Doriaswamy, Marti Hearst, Jon Kleinberg, Kai Krause, Joel Gold, Simone Schnall, Paul Saffo, Lisa Randall, Brian Eno, Giulio Boccaletti, Paul Bloom, Timo Hannay, Anthony Grayling, Matt Ridley, Doug Coupland, Amanda Gefter, Bruce Hood, Gregory Paul, Stephon Alexander, Bart Kosko, John Tooby, Stuart Kauffman, Barry C. Smith, John Naughton, Helen Fisher, Virginia Heffernan, Dimitar Sasselov, Eric Weinstein, Max Tegmark, PZ Myers, Andrew Lih, Christine Finn, Gregory Cochran, John McWhorter, Marco Iacoboni, Raphael Bousso, David Dalrymple, Emily Pronin, Dave Winer, Alanna Conner & Hazel Rose Markus, David Pizarro, Andrian Kreye, David Buss, Carolyn Porco, Dan Sperber, V.S. Ramachandran, Nathan Myhrvold, Charles Simonyi, Richard Thaler, Andrei Linde [Continue to responses.]
Since there are many people on this list who I deeply respect, I generally tend to post some of their responses to the question - I'm sure other readers may favor other responses, so have fun with the list.

One interesting note (and I have read less than half of the responses) is that Paul Bloom (psychologist) and P.Z. Myers (biologist) both chose the same answer: Everything Is The Way It Is Because It Got That Way. 

The three responses shared below are not necessarily people whose work I am familiar with (although Iacoboni is very familiar), but they are responses that resonate with me.

Neuroscientist; Professor of Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine, UCLA; Author, Mirroring People

Like Attracts Like
The beauty of this explanation is twofold. First, it accounts for the complex organization of the cerebral cortex (the most recent evolutionary component of the brain) using a very simple rule. Second, it deals with scaling issues very well, and indeed it also accounts for a specific phenomenon in a widespread human behavior, imitation. It explains how neurons packed themselves in the cerebral cortex and how humans relate to each other. Not a small feat.

Let's start from the brain. The idea that neurons with similar properties cluster together is theoretically appealing, because it minimizes costs associated with transmission of information. This idea is also supported by empirical evidence (it does not always happen that a theoretically appealing idea is supported by empirical data, sadly). Indeed, more than a century of a variety of brain mapping techniques demonstrated the existence of 'visual cortex' (here we find neurons that respond to visual stimuli), 'auditory cortex' (here we find neurons that respond to sounds), 'somatosensory cortex' (here we find neurons that respond to touch), and so forth. When we zoom in and look in detail at each type of cortex, we also find that the 'like attracts like' principle works well. The brain forms topographic maps. For instance, let's look at the 'motor cortex' (here we find neurons that send signals to our muscles so that we can move our body, walk, grasp things, move the eyes and explore the space surrounding us, speak, and obviously type on a keyboard, as I am doing now). In the motor cortex there is a map of the body, with neurons sending signals to hand muscles clustering together and being separate from neurons sending signals to feet or face muscles. So far, so good.

In the motor cortex, however, we also find multiple maps for the same body part (for instance, the hand). Furthermore, these multiple maps are not adjacent. What is going here? It turns out that body parts are only one of the variables that are mapped by the motor cortex. Other important variables are, for instance, different types of coordinated actions and the space sector in which the action ends. The coordinated actions that are mapped by the motor cortex belong to a number of categories, most notably defensive actions (that is, actions to defend one's own body) hand to mouth actions (important to eat and drink!), manipulative actions (using skilled finger movements to manipulate objects). The problem here is that there are multiple dimensions that are mapped onto a two-dimensional entity (we can flatten the cerebral cortex and visualize it as a surface area). This problem needs to be solved with a process of dimensionality reduction. Computational studies have shown that algorithms that do dimensionality reduction while optimizing the similarity of neighboring points (our 'like attracts like' principle) produce maps that reproduce well the complex, somewhat fractured maps described by empirical studies of the motor cortex. Thus, the principle of 'like attracts like' seems working well even when multiple dimensions must be mapped onto a two-dimensional entity (our cerebral cortex).

Let's move to human behavior. Imitation in humans is widespread and often automatic. It is important for learning and transmission of culture. We tend to align our movements (and even words!) during social interactions without even realizing it. However, we don't imitate other people in an equal way. Perhaps not surprisingly, we tend to imitate more people that are like us. Soon after birth, infants prefer faces of their own race and respond more receptively to strangers of their own race. Adults make education and even career choices that are influenced by models of their own race. This is a phenomenon called self similarity bias. Since imitation increases liking, the self similarity bias most likely influences our social preferences too. We tend to imitate others that are like us, and by doing that, we tend to like those people even more. From neurons to people, the very simple principle of 'like attracts like' has a remarkable explanatory power. This is what an elegant scientific explanation is supposed to do. To explain a lot in a simple way.

Consultant, New Scientist; Founding Editor, CultureLab"

Structural Realism
Structural realism—in its metaphysical version, championed by the philosopher of science James Ladyman—is the deepest explanation I know, because it serves as a kind of meta-explanation, one that explains the nature of reality and the nature of scientific explanations.

The idea behind structural realism is pretty simple: the world isn't made of things, it's made of mathematical relationships, or structure. A mathematical structure is a set of isomorphic elements, each of which can be perfectly mapped onto the next. To give a trivial example, the numbers 25 and 52 share the same mathematical structure.

When the philosopher John Worrall first introduced structural realism (though he attributes it to physicist Henri Poincaré), he was trying to explain something puzzling: how was it possible that a scientific theory that would later turn out to be wrong could still manage to make accurate predictions? Take Newtonian gravity. Newton said that gravity was a force that masses exert on one another from a distance. That idea was overthrown by Einstein, who showed that gravity was the curvature of spacetime. Given how wrong Newton was about gravity, it seems almost miraculous that he was able to accurately predict the motions of the planets.

Thankfully, we don't have to resort to miracles. Newton may have gotten the physical interpretation of gravity wrong, but he got a piece of the math right. That's why, at weak masses and small velocities, Einstein's equations reduce to Newton's. The problem, Worrall pointed out, was that we mistook an interpretation of the theory for the theory itself. The fact is, in physics, theories are sets of equations, and nothing more. "Quantum field theory" is a group of mathematical structures. "Electrons" are little stories we tell ourselves.

These days, believing in the reality of objects—of physical things like particles, fields, forces, even spacetime geometries—can quickly lead to profound existential crises.

Quantum theory, for instance, strips particles of any sense of "thingness". One electron is not merely similar to another, all electrons are exactly the same. Electrons have no inherent identity—a fact that makes quantum statistics drastically different from the classical kind. Anyone who believes that an electron is a "thing" in its own right is bound to lose big in a quantum casino.

Meanwhile, all of nature's fundamental forces, including electromagnetism and the nuclear forces that operate deep in the cores of atoms, are described by gauge theory, which shows that forces aren't physical things in the world, but discrepancies in different descriptions of the world, in different observers' points of view. Gravity is a gauge force too, which means you can make it blink out of existence just by changing your frame of reference. In fact, that was Einstein's "happiest thought": a person in freefall can't feel their weight. It's often said that you can't disobey the law of gravity, but the truth is you can take it out with a simple coordinate change.

Recent advances in theoretical physics have only made the situation worse. The holographic principle tells us that our four-dimensional spacetime and everything in it is exactly equivalent to physics taking place on the two-dimensional boundary of the universe. Neither description is more "real" than the other—one can be perfectly mapped onto the other with no loss of information. When we try to believe that spacetime is really four-dimensional or really has a particular geometry, the holographic principle pulls the rug out from under us.

The physical nature of reality has been further eroded by M-theory, the theory that many physicists believe can unite general relativity and quantum mechanics. M-theory encompasses five versions of string theory (plus one non-stringy theory known as supergravity) all of which are related by mathematical maps called dualities. What looks like a strong interaction in one theory looks like a weak interaction in another. What look like eleven dimensions in one theory look like ten in another. Big can look like small, strings can look like particles. Virtually any object you can think of will be transformed into something totally different as you move from one theory to the next—and yet, somehow, all of the theories are equally true.

This reality crisis has grown so dire that Stephen Hawking has called for a kind of philosophical surrender, a white flag he terms "model-dependent realism", which basically says that while our theoretical models offer possible descriptions of the world, we'll simply never know the true reality that lies beneath. Perhaps there is no reality at all.

But structural realism offers a way out. An explanation. A reality. The only catch is that it's not made of physical objects. Then again, our theories never said it was. Electrons aren't real, but the mathematical structure of quantum field theory is. Gauge forces aren't real, but the symmetry groups that describe them are. The dimensions, geometries and even strings described by any given string theory aren't real—what's real are the mathematical maps that transform one string theory into another.

Of course, it's only human to want to interpret mathematical structure. There's a reason that "42" is hardly a satisfying answer to life, the universe and everything. We want to know what the world is really like, but we want it in a form that fits our intuitions. A form that means something. And for our narrative-driven brains, meaning comes in the form of stories, stories about things. I doubt we'll ever stop telling stories about how the universe works, and I, for one, am glad. We just have to remember not to mistake the stories for reality.

Structural realism forces us to radically revise the way we think about the universe. But it also provides a powerful explanation for some of the most mystifying aspects of physics. Without it, we'd have to give up on the notion that scientific theories can ever tell us how the world really is. And that, in my humble opinion, makes it a pretty beautiful explanation.

Director, Cambridge Embodied Cognition and Emotion Laboratory; University Lecturer, Department of Social and Developmental Psychology Cambridge

Embodied Metaphors Unify Perception, Cognition and Action
Philosophers and psychologists grappled with a fundamental question for quite some time: How does the brain derive meaning? If thoughts consist of the manipulation of abstract symbols, just like computers are processing 0s and 1s, then how are such abstract symbols translated into meaningful cognitive representations? This so-called "symbol grounding problem" has now been largely overcome because many findings from cognitive science suggest that the brain does not really translate incoming information into abstract symbols in the first place. Instead, sensory and perceptual inputs from every-day experience are taken in their modality-specific form, and they provide the building blocks of thoughts.

British empiricists such as Locke and Berkeley long ago recognized that cognition is inherently perceptual. But following the cognitive revolution in the 1950ies psychology treated the computer as the most appropriate model to study the mind. Now we know that a brain does not work like a computer. Its job is not to store or process information; instead, its job is to drive and control the actions of the brain's large appendage, the body. A new revolution is taking shape, considered by some to bring an end to cognitivism, and giving way to a transformed kind of cognitive science, namely an embodied cognitive science.

The basic claim is thatthe mind thinks in embodied metaphors. Early proponents of this idea were linguists such as George Lakoff, and in recent years social psychologists have been conducting the relevant experiments, providing compelling evidence. But it does not stop here; there is also a reverse pathway: Because thinking is for doing, many bodily processes feed back into the mind to drive action.

Consider the following recent findings that relate to the very basic spatial concept of verticality. Because moving around in space is a common physical experience, concepts such as "up" or "down" are immediately meaningful relative to one's own body. The concrete experience of verticality serves as a perfect scaffold for comprehending abstract concepts, such as morality: Virtue is up, whereas depravity is down: Good people are "high minded" and "upstanding" citizens, whereas bad people are "underhanded" and the "low life" of society. Recent research by Brian Meier, Martin Sellbom and Dustin Wygant illustrated that research participants are faster to categorize moral words when they are presented in an up location, and immoral words when they are presented in a down location. Thus, people intuitively relate the moral domain to verticality; however, Meier and colleagues also found that peoplewho do not recognize moral norms, namely psychopaths, fail to do so, and do not show this effect.

People not only think of all things good and moral as up, but they also think of God as up, and the Devil as down. Further, those in power are conceptualized as being high up relative to those down below over whom they hover and exert control, as shown by Thomas Schubert.All the empirical evidence suggests that there is indeed a conceptual dimension that leads up, both literally and metaphorically. This vertical dimension that pulls the mind up to considering what higher power there might be is deeply rooted in the very basic physical experience of verticality.

However, verticality not only influences people's representation of what is good, moral and divine, but movement through space along the vertical dimension can even change their moral actions. Larry Sanna, Edward Chang, Paul Miceli and Kristjen Lundberg recently demonstrated that manipulating people's location along the vertical dimension can actually turn them into more "high minded" and "upstanding" citizens. They found that people in a shopping mall who had just moved up an escalator were more likely to contribute to a charity donation box than people who had moved down on the escalator. Similarly, research participants who had watched a film depicting a view from high above, namely flying over clouds seen from an airplane window subsequently showed more cooperative behaviour than participants who had watched a more ordinary, and less "elevating" view from a car window. Thus, being physically elevated induced people to act on "higher" moral values.

The growing recognition that embodied metaphors provide one common language of the mind has lead to fundamentally different ways of studying how people think. For example, under the assumption that the mind functions like a computer psychologists hoped to figure out how people think by observing how they play chess, or memorize lists of random words. From an embodied perspective it is evident that such scientific attempts were hopelessly doomed to fail. Instead, it is increasingly clear that cognitive operations of any creature, including humans, have to solve certain adaptive challenges of the physical environment. In the process, embodied metaphors are the building blocks of perception, cognition, and action. It doesn't get much more simple and elegant than that.
That's enough for now - I'll likely post some more of these as I have time.

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