I recently looked at Al Roth’s web page on “Game Theory, Experimental Economics, and Market Design” which is probably the best link collection on the web on these issues. What caught my eye was the nonchalant unusual combination of “Game theory” and “experimental economics”. From a CS point of view, we rarely see someone who is both a theoretician and also does “experimental-anything”. Al Roth’s reasoning for this combination is very simple: “My research is in game theory, experimental economics, and market design (for which game theory, experimentation, and computation are complementary tools)”.
So, should “algorithmic game theory” (in the broad sense) also put significant energy into experimentation? Should we specifically study the interaction of humans with our systems? My original point of view was that luckily we are spared the difficulty of dealing with these pesky humans. As we study rational behavior of fully controlled computer systems, we get to design their behavior and we will certainly design them to be perfectly rational according to our best analysis (the buzzword is “hyper-rational”). Thus if our analysis suggests that the rational behavior when working under protocol X is to do Y, then we will just program our software to do so — why shouldn’t we? Of course, there could be various technical challenges (computational limitation, partial information, etc) but these we can analyse and quantify and handle as well as is possible. “Rational Choice” debates about the relevance of game theory to human behavior concern economists — not us.
The problem is of course at the boundary of the computerized system: how are the utilities specified? A well-designed computerized system can act rationally to optimize a given goal, but it must be given this goal by humans. This is not just a conceptual difficulty, but actually the main challenge in most systems that I know. Elicitation of user preferences via some kind of a user interface is a main technical challenge. Consider software that is used for participating in some (not too simple) auction such as the adwords auction. While there are usually many interesting algorithmic and game-theoretic considerations in designing the bidding software (and the auction itself), I would say that the most important design bottleneck is still the user-interface: how do we let the user specify what he wants to get in the auction in an intuitive yet powerful way. Part of the problem is that “what the user wants” has different meanings: one of them is imprecise and sits in his head, while the other is formal and sits in the software. All too often optimizing for the latter does not do so for the former. This brings the framing effect into play in a direct technical sense: what users will seem to want depends on how things are presented to them. While I can see some companies designing their software as to “push” people towards behavior that optimizes the company’s revenue, it is not clear to me what should our normative goals be in the design of such user interfaces.
I don’t have a conclusion to end this post, so instead here are two related comments:
- I never quite understood the difference between experimental economics and behavioral economics. My impression is that it is simply a question of your attitude towards game theory: experimental-pro, behavioral-con. The anti-game-theory bias is probably not that of its founders Kahneman and Tversky. Shortly after winning the Nobel prize in economics in 2002, I heard Kahneman talk at a dinner held by the Hebrew University’s rationality center. His point was that while most psychologists would immediately dismiss the economic assmptions of rationality as absurd regarding human beings, the greatness of his co-author Tversky was to realize that there was an important underlying truth to this point of view, and hence that it was interesting to carefully study its limitations.
- The experimental vs. theoretical question is part of a much broader set of issues of the theory-vs-practice family. It seems that algorithmic game theory sits in an interesting cross-roads where we get many perspectives on these issues: from CS, from economics, the wider rational choice debate, the actual Internet, etc.