Cooperation Among Strangers: Algorithmic Enforcement of Reciprocal Exchange with Blockchain-Based Smart Contracts

Enhancing cooperation among strangers is challenging. Strangers, who lack previous interactions and trust, cannot rely on human reciprocity as they engage in social and economic exchange. They have instead a tendency to defect for maximizing individual interests rather than to cooperate for benefiting each party in the exchange. Blockchain-based smart contracts come with the promise of solving this dilemma of cooperation. In this paper, we trace this promise to a new mechanism of cooperation, programmed reciprocity, defined as coded instructions for automatically returning good for good (positive reciprocity) and ill for ill (negative reciprocity). Programmed reciprocity is rooted in the algorithmic enforcement capability of blockchain networks, defined as the ability to guarantee the execution of the rules of an exchange agreement without a central authority and the possibility of human interference by either of the involved parties. We propose that algorithmic enforcement capability positively affects the viability of cooperation among strangers on the blockchain through programmed reciprocity. This is contingent on the level of contract complexity and blockchain confidence. Our proposed framework extends the nascent literature on blockchain governance with a novel explanation of how programmed reciprocity can enhance cooperation among strangers. In doing this, it also addresses a significant yet unresolved problem in the literature on cooperation in social and economic exchanges.