Recently, Gary Kasparov wrote an essay about humans and computers playing chess, under the guise of a book review. Andrew McAfee today published an essay on Kasparov’s ideas, with a specific focus on one observation by Kasparov.
Kasparov noted that recent matches have shown that weak human chess players with computers can beat a chess supercomputer, and, in addition, a chess grandmaster with a computer but a weak organization of the human-computer collaboration. In Kasparov’s words,
Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.
McAfee starts from this and says that Kasparov may have stumbled upon a better model of business processes. From my point of view, I see Kasparov’s insight as one example of the great benefit to be gotten if we can only adapt mechanism design theory to capture the fuzziness of humans and the precision of computers, acting in tandem, better. (I think there are many examples to urge us to change mechanism design towards more human-compatible decision-making models, on which I plan to blog more.)
I am making no grand claim that I know how we can approach this goal. I am simply noting that it seems a very worthy goal, one that I would rather see research in mechanism design aim for. Instead, the current thrust of the mainstream mechanism design research seems to be to get more and more refined mathematical results based on the assumption that the actors in the mechanisms studied, whether human or computer agents, behave with the precision of computers. I am aware of some work that attempts to introduce errors in the decision-making of agents in mechanism design theory, such as work by Kfir Eliaz, but I would certainly love it if more of the very clever mechanism theorists attacked the fuzziness problem head on.
Let us not leave the topic of a better business process to Harvard Business Review articles only. Some Econometrica articles on it, please.