ICES: Small: Impartial decision making in distributed systems

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Conflicts of interest pervade collective decision-making among peers. Such conflicts can be modeled as the tension between two distinct components of an agent's evaluation of the final outcome: her selfish interest and her disinterested opinion. When those two orderings are logically separated, sometimes a rule can be designed that aggregates individual opinions while preventing an agent's message having any impact on her selfish welfare. Such a rule is called impartial. This project focuses on two simple problems, the award of an indivisible private good (a prize) and peer ranking, when agents care selfishly only about winning the prize, or their own ranking. There exist fairly simple voting rules where your vote cannot make you win or lose the prize, yet it influences who wins if you do not. It is also possible to design a peer ranking system where an agent has no influence on his own ranking, but contributes to that of his peers. Some of the impartial decision rules to which the project is devoted resemble familiar voting rules such as qualified majorities, or the median vote on a line. One output of the research consists of practical mechanisms as universally applicable as any other voting rule. Another direction is to ask which general patterns of selfish interest versus selfless opinions allow for impartial rules, and which do not. The project contributes to the broad stream of economics research on mechanism design concentrating on the strategic distortions of information revelation.Peer evaluation is a central institution in business partnerships, academic communities, and virtually any community sharing specialized knowledge. Evaluating specialized work requires knowledge that can only be found among those experts; it cannot be entrusted to an impartial but clueless outside observer. Academics pick some of their own for Nobel prizes, and movie professionals award the Oscars. Peer evaluations are vulnerable to conflicts of interest: a participant may be tempted to corrupt her disinterested opinion (a valuable piece of information to determine the correct decision) to serve her selfish interests, which by contrast are often useless to the group. Some examples of such corruption are easy to avoid: judges in sports competitions should not rank athletes of their own countries, spouses cannot testify for or against each other, etc. More subtle ones, such as the multiplication of fake (favorable or critical) reviews on the Internet can only be avoided by the clever design of the evaluation process. This project aims to construct a handful of decision mechanisms immune to conflicts of interest, applicable directly to the division of money between business partners, the award of a prize among peers, and the ranking of Universities by their own students and alumni. This foundational research has potential for much broader impact in the setting of the Internet, where peer evaluations are ubiquitous- from reputation scores for electronic traders (on EBay or Amazon), to the users of social networks (Epinions, Twitter), and the scoring and ranking systems of web pages by search engines, relying exclusively on the pattern of mutual links between pages.