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AI systems are breaking an internet that was designed at human-scale — by making it cheaper than ever to coordinate, transact, and generate voice, video, and text that are increasingly indistinguishable from human activity. We’re already beset w
Decentralized autonomous organizations (DAOs) regularly negotiate with external counterparties — vendors, regulators, protocol developers. DAOs aggregate the preferences of their individual stakeholders to negotiate collectively as a group. To study these and related negotiation contexts, Peter Buisseret (Harvard University) analyzes a dynamic bargaining game in which a heterogeneous group negotiates jointly with a single external agent — such as a regulator or an employer. Group members have different valuations from reaching an agreement with the agent, and they are uncertain about the agent’s resolve. Regardless of how power is distributed across group members, and regardless of their primitive values from agreement, all group members favor more aggressive offers than they would if they negotiated alone. These aggressive offers not only extract concessions when the agent is weak, but they also reveal information about the agent’s resolve if they are rejected. This information reduces conflicts amongst group members over their subsequent negotiating strategy, to the benefit of all members. Delegation of power to lower-valuation members may increase the probability of an agreement.
About the presenter
Peter is an Assistant Professor of Government at Harvard University. His research uses game theory to study electoral competition, legislative policymaking, and collective bargaining. His broader agenda focuses on how political institutions structure political and economic incentives, and how they can be improved.
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