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We study a scenario where an adjudication task (e.g., the resolution of abinary dispute) is outsourced to a set of agents who are appointed as jurors.This scenario is particularly relevant in a Web3 environment, where noverification of the adjudication outcome is possible, and the appointed agentsare, in principle, indifferent to the final verdict. We consider simpleadjudication mechanisms that use (1) majority voting to decide the finalverdict and (2) a payment function to reward the agents with the majority voteand possibly punish the ones in the minority. Agents interact with such amechanism strategically: they exert some effort to understand how to properlyjudge the dispute and cast a yes/no vote that depends on this understanding andon information they have about the rest of the votes. Eventually, they vote sothat their utility (i.e., their payment from the mechanism minus the cost dueto their effort) is maximized. Under reasonable assumptions about how anagent's effort is related to her understanding of the dispute, we show thatappropriate payment functions can be used to recover the correct adjudicationoutcome with high probability. Our findings follow from a detailed analysis ofthe induced strategic game and make use of both theoretical arguments andsimulation experiments.

Outsourcing Adjudication to Strategic Jurors