119 How the Mind Works STEVEN PINKER Director, McDonnell-Pew Center for Cognitive Neuroscience, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA The human mind is a remarkable organ. It has allowed us to walk on the moon, to discover the physical basis of life and the universe, and to play chess almost as well as a computer. But the brain raises a paradox. On the one hand, many tasks that we take for granted���walking around a room, picking up an object, recognizing a face, remembering information���are feats that scientists and engineers have been unable to duplicate in robots and computers. Nonetheless, these feats can be accomplished by any four-year-old, and we tend to be blas�� about them. On the other hand, for all its engineering excellence, the mind has many apparent quirks. For example, why is the thought of eating worms disgusting when worms are perfectly safe and nutri- tious? Why do men do insane things like challenge each other to duels and murder their ex-wives? Why do fools fall in love? Why do people believe in ghosts and spirits? Recently, I have been foolhardy enough to try to answer questions like this in a book called How the Mind Works. What I will be talking about today comes from that book, which is based on three key ideas: computation, evolution, and specialization. The first idea is that the function of the brain is information processing, or com- putation. Computation involves an age-old problem, one that was raised by Profes- sor Edelman, namely, Descartes���s problem of the causation of behavior. If I were to ask you, ���Why did Bill just get on the bus?��� to answer that question you wouldn���t run a neural network simulation and you wouldn���t need to put Bill���s head in a scan- ner. You could just ask Bill, and you might discover that the explanation for his be- havior is that he wants to visit his grandmother, and he knows that the bus will take him to his grandmother���s house. No science of the future is likely to provide an ex- planation with greater predictive power than that. If Bill hated the sight of his grand- mother or if he knew the route had changed, his body would not be on that bus. But this excellent theory raises a puzzle. The beliefs and desires that cause Bill���s behav- ior are colorless, odorless, tasteless, and weightless. Nevertheless, they are as potent a cause of action as any billiard ball clacking into another billiard ball. How do we explain this seeming paradox? One part of the solution, I believe, is that beliefs and desires are information. Information is another commodity that is colorless, odorless, tasteless, and weightless yet can have physical effects without resorting to any occult or mysterious process. Information consists of patterns in matter or energy, namely symbols, that correlate with states of the world. That���s what we mean when we say that something carries information. A second part of the solution is that beliefs and desires have their effects in computation���where compu- tation is defined, roughly, as a process that takes place when a device is arranged so that information (namely, patterns in matter or energy inside the device) causes changes in the patterns of other bits of matter or energy, and the process mirrors the

120 ANNALS NEW YORK ACADEMY OF SCIENCES laws of logic, probability, or cause and effect in the world. The result is that if the old patterns are accurate or true, or correlate with some aspect of reality, the new ar- rangements of matter or energy will as well. The cascade gives the device an ability to deduce new truths from old truths, which is not a bad definition of thinking. In fact, the computational theory of mind is the only theory that I know of that can ex- plain how it is that patterns of physical change in a device���be it a computer or a brain, or, for that matter, some extraterrestrial intelligent life���might accomplish something we would dignify with the term ���thinking.��� It���s the only explanation we have for how physical changes actually do something we would be willing to call intelligent. It is an explanation of where intelligence comes from. A few comments must be added to this claim. One is that the computational the- ory of mind is very different from the computer metaphor that Professor Edelman has alluded to in his presentation. As he pointed out, there are many ways in which commercially available computers are radically different from brains. Computers are serial brains are parallel. Computers are fast brains are slow. Computers have de- terministic components brains have noisy components. Computers are assembled by an external agent brains have to assemble themselves. Computers display screen- savers with flying toasters brains do not. But the claim is not that commercially available computers are a good model for the brain. Rather, the claim is that the an- swer to the question ���What makes brains intelligent?��� may overlap with the question ���What makes computers intelligent?��� The common feature, I suggest, is informa- tion-processing, or computation. An analogy is that when we want to understand how birds fly, we invoke principles of aerodynamics that also apply to airplanes. But that doesn���t mean that we are committed to an airplane metaphor for birds and should ask whether birds have complimentary beverage service. It���s a question of isolating the key component of the best explanation. Another comment is that the computational theory of mind, explicitly or not, has set the agenda for brain science for decades. An old example from introductory neu- roscience classes describes the naive person who asks, ���Since the image on the retina is upside-down but we see the world right-side up, is there some part of the brain that turns the image right-side up?��� We all realize that this question rests on a fallacy, that there is no such process in the brain, and that there doesn���t need to be any such pro- cess. Why is it a fallacy? Because the orientation of the image on the retina makes no difference to how the brain processes information. Since information-processing is the relevant aspect of what goes on in the brain, the orientation on the retina���and, for that matter, on the visual cortex���is irrelevant that is why the above is a pseudoquestion. Similarly, the search for the neural basis of psychological functions is guided, from beginning to end, by invoking information-processing. As you know, one of the great frontiers of science is the search for the molecular basis of learning and memory. Well, of the hundreds or thousands of metabolic processes in the brain, how will we know when we���ve identified the one that corresponds to memory? We will know we have it when the process meets the requirements of the storage and re- trieval of information. So again, it is information that sets the interesting questions in neuroscience. A third comment is that the computational theory of mind is a radical challenge to our everyday way of thinking about the mind, because the theory says that the life- blood of thought is information. That goes against our folk notion that the lifeblood