This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

According to Margaret Gilbert’s collective epistemology, we should take attributions of beliefs to groups seriously, rather than metaphorically or as reducible to individual belief. I argue that, similarly, attributions of belief to markets ought to be taken seriously and not merely as reports of the average beliefs of market participants. While many of Gilbert’s purported examples of group belief are better thought of as instances of acceptance, some collectives, such as courts and markets, genuinely believe. Such collectives enact truth-aimed processes (...) that are beyond the control of any single individual. These processes produce beliefs that are distinct from any individual belief and do not merely report the “average” or “majority” view of the group. In the case of markets, beliefs are indicated by prices, though it is often difficult to infer beliefs from prices and those inferences are almost always uncertain. Reliabilism is the best available standard of justification for market beliefs. In some cases market beliefs are reliable and prove to be true. Thus, in some cases markets can know. (shrink)

According to Margaret Gilbert’s collective epistemology, we should take attributions of beliefs to groups seriously, rather than metaphorically or as reducible to individual belief. I argue that, similarly, attributions of belief to markets ought to be taken seriously and not merely as reports of the average beliefs of market participants. While many of Gilbert’s purported examples of group belief are better thought of as instances of acceptance, some collectives, such as courts and markets, genuinely believe. Such collectives enact truth-aimed processes (...) that are beyond the control of any single individual. These processes produce beliefs that are distinct from any individual belief and do not merely report the “average” or “majority” view of the group. In the case of markets, beliefs are indicated by prices, though it is often difficult to infer beliefs from prices and those inferences are almost always uncertain. Reliabilism is the best available standard of justification for market beliefs. In some cases market beliefs are reliable and prove to be true. Thus, in some cases markets can know. (shrink)

Prediction markets, which trade contracts based on the results of predictions, have been remarkably successful in predicting the results of political events. A number of proposals have been made to extend prediction markets to scientific questions, and some small-scale science prediction markets have been implemented. Advocates for science prediction markets argue that they could alleviate problems in science such as bias in peer review and epistemically unjustified consensus. I argue that bias in peer review and epistemically unjustified consensuses are genuine (...) problems in science, and that current attempts to solve them fail in practical circumstances. Prediction markets do show some promise for answering scientific questions while avoiding the pitfalls of consensus and peer review. However, there are strong reasons to believe that science prediction markets will not perform nearly so well as election prediction markets, and implementing prediction markets on a large scale could have significant unintended consequences for the organization of scientific research. The promise of prediction markets to solve current problems in assessing scientific claims is therefore largely illusory. (shrink)