Making markets and democracy work: a story of incentives and computing

Collective choice settings are the heart of society. Game theory provides a basis for engineering the incentives into the interaction mechanism (e.g., rules of an election or auction) so that a desirable system-wide outcome (e.g., president, resource allocation, or task allocation) is chosen even though every agent acts based on self-interest. However, there are a host of computer science issues not traditionally addressed in game theory that have to be addressed in order to make mechanisms work in the real world. Those computing, communication, and privacy issues are deeply intertwined with the economic incentive issues. For example, the fact that agents have limited computational capabilities to determine their own (and others') preferences ruins the incentive properties of established auction mechanisms, and gives rise to new issues. On the positive side, computational complexity can be used as a barrier to strategic behavior in settings where economic mechanism design falls short. Novel computational approaches also enable new economic institutions. For example, market clearing technology with specialized search algorithms is enabling a form of interaction that I call expressive competition. As another example, selective incremental preference elicitation can determine the optimal outcome while requiring the agents to determine and reveal only a small portion of their preferences. Furthermore, automated mechanism design can yield better mechanisms than the best known to date.