Proceedings Abstracts of the Twenty-Fourth International Joint Conference on Artificial Intelligence

Impartial Peer Review / 582
David Kurokawa, Omer Lev, Jamie Morgenstern, Ariel D. Procaccia

Motivated by a radically new peer review system that the National Science Foundation recently experimented with, we study peer review systems in which proposals are reviewed by PIs who have submitted proposals themselves. An (m, k)-selection mechanism asks each PI to review m proposals, and uses these reviews to select (at most) k proposals. We are interested in impartial mechanisms, which guarantee that the ratings given by a PI to others' proposals do not affect the likelihood of the PI's own proposal being selected. We design an impartial mechanism that selects a k-subset of proposals that is nearly as highly rated as the one selected by the non-impartial (abstract version of) the NSF pilot mechanism, even when the latter mechanism has the "unfair" advantage of eliciting honest reviews.