Carlo Martini

At least since Kuhn’s Structure, philosophers have studied the influence of social factors in science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social organization of science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used in science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold.

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.

This paper applies the theory of networks to the problem of how agents should assign weights to other agents in the Lehrer-Wagner model for consensus formation. The Lehrer- Wagner theory of consensus is introduced, and the problem of weight assignment is highlighted as one of the open prob- lems for the theory. The paper argues that the application of the theory of networks to the Lehrer-Wagner model con- stitutes an interesting and fruitful option, among others, for the problem of weight assignment

This paper explores the scope and limits of rational consensus through mutual respect, with the primary focus on the best known formal model of consensus: the Lehrer–Wagner model. We consider various arguments against the rationality of the Lehrer–Wagner model as a model of consensus about factual matters. We conclude that models such as this face problems in achieving rational consensus on disagreements about unknown factual matters, but that they hold considerable promise as models of how to rationally resolve non-factual disagreements.

The claim that diversity and independence have a net positive epistemic effect on the judgments of groups has been recently defended formally by Scott Page, among others, and popularized in Surowiecki's The Wisdom of Crowds. In Meta-Induction and the Wisdom of Crowds Thorn and Schurz take issue with the claim that more diversity and independence in groups leads to better collective judgments. I argue that Thorn and Schurz's arguments are helpful in clarifying a number of over-generalizations about diversity and independence that are often circulated in the social epistemology literature. I also argue that the relevant formal arguments are easily misunderstood when presented 'in a vacuum', that is, without a context of application in mind. I provide a different approach to understanding formal results in social epistemology: With the help of concrete scenarios and the formal literature, I focus on a trade-off between independence and dependence in groups. I show that the approach works well also for another principle in social epistemology; namely, the principle that 'more heads are better than few'.