Ryan Muldoon

Very diverse societies pose real problems for Rawlsian models of public reason. This is for two reasons: first, public reason is unable accommodate diverse perspectives in determining a regulative ideal. Second, regulative ideals are unable to respond to social change. While models based on public reason focus on the justification of principles, this book suggests that we need to orient our normative theories more toward discovery and experimentation. The book develops a unique approach to social contract theory that focuses on diverse perspectives. It offers a new moral stance that author Ryan Muldoon calls, "The View From Everywhere," which allows for substantive, fundamental moral disagreement. This stance is used to develop a bargaining model in which agents can cooperate despite seeing different perspectives. Rather than arguing for an ideal contract or particular principles of justice, Muldoon outlines a procedure for iterated revisions to the rules of a social contract. It expands Mill's conception of experiments in living to help form a foundational principle for social contract theory. By embracing this kind of experimentation, we move away from a conception of justice as an end state, and toward a conception of justice as a trajectory.

In this paper we argue that there is a kind of moral disagreement that survives the Rawlsian veil of ignorance. While a veil of ignorance eliminates sources of disagreement stemming from self-interest, it does not do anything to eliminate deeper sources of disagreement. These disagreements not only persist, but transform their structure once behind the veil of ignorance. We consider formal frameworks for exploring these differences in structure between interested and disinterested disagreement, and argue that consensus models offer us a solution concept for disagreements behind the veil of ignorance.

Because of its complexity, contemporary scientific research is almost always tackled by groups of scientists, each of which works in a different part of a given research domain. We believe that understanding scientific progress thus requires understanding this division of cognitive labor. To this end, we present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to climb uphill in this landscape, where elevation represents the significance of the results discovered by employing a research approach. We consider three different search strategies scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community as a whole influence their actions. This is compared with two social research strategies, which we call the follower and maverick strategies. Followers are biased towards what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform both of the other strategies. Finally, we show that in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains.

InOn Liberty, Mill introduced the concept of ‘experiments in living’. I will provide an account of what Mill saw to be the basic problem he was addressing – the extensive pressure to fit in with the crowd, and how this bred mediocrity. I connect this to worries about public reason models of justification. I argue that a generalized version of Mill's argument offers us a better path to political justification stemming from experimentation. Rather than grounding political justification on shared political reasons, we justify our political culture on our ability to reject consensus views and try alternatives.

Previous literature has demonstrated the important role that trust plays in developing and maintaining well-functioning societies. However, if we are to learn how to increase levels of trust in society, we must first understand why people choose to trust others. One potential answer to this is that people view trust as normative: there is a social norm for trusting that imposes punishment for noncompliance. To test this, we report data from a survey with salient rewards to elicit people’s attitudes regarding the punishment of distrusting behavior in a trust game. Our results show that people do not behave as though trust is a norm. Our participants expected that most people would not punish untrusting investors, regardless of whether the potential trustee was a stranger or a friend. In contrast, our participants behaved as though being trustworthy is a norm. Most participants believed that most people would punish someone who failed to reciprocate a stranger’s or a friend’s trust. We conclude that, while we were able to reproduce previous results establishing that there is a norm of reciprocity, we found no evidence for a corresponding norm of trust, even among friends.