The World Chess Championship is underway, and the current champion – the Indian Viswanathan Anand – is trailing his young rival Magnus Carlsen by three to five. In the opinion of many, Carlsen is set fair to become the strongest ever human player.
The match is an absorbing spectacle, but the game of chess is not just interesting in its own right. It tells us a great deal about the nature of the environment in which individuals and firms make decisions, and how these decisions are actually made. Herbert Simon, possibly the greatest social scientist of the second half of the twentieth century, used chess to illustrate his key ideas about decision making.
Simon won the Nobel Prize in economics. He also received the Turing Award for his contributions to artificial intelligence, and the American Psychological Association conferred on him an prize for his Outstanding Lifetime Contributions to Psychology. His day job, as it were, was as professor of industrial management at Carnegie Mellon.
Simon believed that the way in which economists assume people take decisions was profoundly wrong. A Rational Economic Person gathers large amounts of information on the alternative choices available in any particular situation, compares them to his or her preferences, and then makes the best possible decision – the “optimal”, as economists say. But Simon argued that, in most situations, the environment is so complex that the optimal decision can never be known. Instead, we use what he called “rules of thumb”: simple rules which give reasonably satisfactory outcomes – until they do not.
This is not merely of academic interest. The economic models in both finance ministries and central banks are based on the concept of rational decision making. A great deal of regulation is designed to correct so-called deviations from “rational” behaviour, both by consumers and firms. How does this relate to chess?
The game of chess is in principle very simple. There are about a dozen rules, which can be learned easily. The object of the game is unequivocal, to capture the opponent’s King. And you know everything your opponent has done. But in most situations in the game, the optimal move cannot be computed. Many bad options can be eliminated, and players like Carlsen will do this much more effectively than an average player. Even at world championship level, this is how most games are lost and won. It is not often a matter of superior rational calculation of the consequences of a move. It is the judgment about what constitutes a good move.
Do computers help? In chess, all possible positions with six pieces have now been solved. But there are 32 pieces, and the computational complexity scales super-exponentially with the addition of each piece.
The environment in which firms operate is also enormously more complicated than the game of chess. Competitors, for example, can innovate and invent entirely new pieces and new rules. We live in a radically uncertain world in which, as John Maynard Keynes once remarked, “we have, as a rule, only the vaguest idea of any but the most direct consequences of our acts.”
Paul Ormerod
