The chapter reviews recent theoretical and empirical developments concerning the theory of team reasoning in game theoretic interactions.

Against the orthodox view of the Nash equilibrium as “the embodiment of the idea that economic agents are rational” (Aumann, 1985, p 43), some theorists have proposed ‘non-classical’ concepts of rationality in games, arguing that rational agents should be capable of improving upon inefficient equilibrium outcomes. This paper considers some implications of these proposals for economic theory, by focusing on institutional design. I argue that revisionist concepts of rationality conflict with the constraint that institutions should be designed to be incentive-compatible, (...) that is, that they should implement social goals in equilibrium. To resolve this conflict, proponents of revisionist concepts face a choice between three options: (1) reject incentive compatibility as a general constraint, (2) deny that individuals interacting through the designed institutions are rational, or (3) accept that their concepts do not cover institutional design. I critically discuss these options and I argue that a more inclusive concept of rationality, e.g. the one provided by Robert Sugden’s version of team reasoning, holds the most promise for the non-classical project, yielding a novel argument for incentive compatibility as a general constraint. (shrink)

We propose a methodology for normative evaluation when preferences are context-dependent. We offer a precise definition of context-dependence and formulate a normative criterion of self-determination, according to which one situation is better than another if individuals are aware of more potential contexts of a choice problem. We provide two interpretations of our normative approach: an extension of Sugden’s opportunity criterion and an application of Sen’s positional views in his theory of justice. Our proposition is consistent with Muldoon’s and Gaus’ approaches (...) of public reason in social contract theory, which account for the diversity of perspectives in non-ideal worlds. (shrink)

Standard game theory cannot explain the selection of payoff-dominant outcomes that are best for all players in common-interest games. Theories of team reasoning can explain why such mutualistic cooperation is rational. They propose that teams can be agents and that individuals in teams can adopt a distinctive mode of reasoning that enables them to do their part in achieving Pareto-dominant outcomes. We show that it can be rational to play payoff-dominant outcomes, given that an agent group identifies. We compare team (...) reasoning to other theories that have been proposed to explain how people can achieve payoff-dominant outcomes, especially with respect to rationality. Some authors have hoped that it would be possible to develop an argument that it is rational to group identify. We identify some large—probably insuperable—problems with this project and sketch some more promising approaches, whereby the normativity of group identification rests on morality. (shrink)

This paper examines two strands of literature regarding economic models of cooperation. First, payoff transformation theories assume that people may not be exclusively motivated by self-interest, but also care about equality and fairness. Second, team reasoning theorists assume that people might reason from the perspective of the team, rather than an individualistic perspective. Can these two theories be unified? In contrast to the consensus among team reasoning theorists, I argue that team reasoning can be viewed as a particular type of (...) payoff transformation. However, I also demonstrate that many payoff transformations yield actions that team reasoning rules out. (shrink)

We cooperate with other people despite the risk of being exploited or hurt. If future artificial intelligence (AI) systems are benevolent and cooperative toward us, what will we do in return? Here we show that our cooperative dispositions are weaker when we interact with AI. In nine experiments, humans interacted with either another human or an AI agent in four classic social dilemma economic games and a newly designed game of Reciprocity that we introduce here. Contrary to the hypothesis that (...) people mistrust algorithms, participants trusted their AI partners to be as cooperative as humans. However, they did not return AI's benevolence as much and exploited the AI more than humans. These findings warn that future self-driving cars or co-working robots, whose success depends on humans' returning their cooperativeness, run the risk of being exploited. This vulnerability calls not just for smarter machines but also better human-centered policies. (shrink)