I examine how particular social arrangements and incentive structures encourage the honest reporting of experimental results and minimize fraudulent scientific work. In particular I investigate how epistemic communities can achieve this goal by promoting members to police the community. Using some basic tools from game theory, I explore a simple model in which scientists both conduct research and have the option of investigating the findings of their peers. I find that this system of peer policing can in many cases ensure (...) high levels of honesty. (shrink)

An a priori thesis about evidence, defended by many, states that the only empirical fact that can affect the truth of an objective evidence claim of the form ‘e is evidence for h’ (or ‘e confirms h to degree r’) is the truth of e; all other considerations are a priori. By examining cases involving evidential flaws, I challange this claim and defend an empirical concept of evidence. In accordance with such a concept, whether, and the extent to which, e, (...) if true, confirms h is an empirical, not a priori, fact. (shrink)

Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its (...) members are less aware of their colleagues' experimental results. Second, there is a robust tradeoff between the reliability of a community and the speed with which it reaches a correct conclusion. ‡The author would like to thank Brian Skyrms, Kyle Stanford, Jeffrey Barrett, Bruce Glymour, and the participants in the Social Dynamics Seminar at University of California–Irvine for their helpful comments. Generous financial support was provided by the School of Social Science and Institute for Mathematical Behavioral Sciences at UCI. †To contact the author, please write to: Department of Philosophy, Baker Hall 135, Carnegie Mellon University, Pittsburgh, PA 15213-3890; e-mail: [email protected]. (shrink)

Conformity is an often criticized feature of human belief formation. Although generally regarded as a negative influence on reliability, it has not been widely studied. This paper attempts to determine the epistemic effects of conformity by analyzing a mathematical model of this behavior. In addition to investigating the effect of conformity on the reliability of individuals and groups, this paper attempts to determine the optimal structure for conformity. That is, supposing that conformity is inevitable, what is the best way for (...) conformity effects to occur? The paper finds that in some contexts conformity effects are reliability inducing and, more surprisingly even when it is counterproductive, not all methods for reducing its effect are helpful. These conclusions contribute to a larger discussion in social epistemology regarding the effect of social behavior on individual reliability. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? Michael Strevens provides a partial answer to these questions by showing that scientists should be willing to sign a social contract that mandates sharing. However, he also argues that it is not in an individual credit-maximizing scientist's interest to follow this norm. I argue against Strevens that individual scientists can rationally conform to the communist norm, even (...) in the absence of a social contract or other ways of socially enforcing the norm, by proving results to this effect in a game-theoretic model. This shows that the incentives provided to scientists through the priority rule are sufficient to explain both the origins and the persistence of the communist norm, adding to previous results emphasizing the benefits of the incentive structure created by the priority rule. (shrink)

Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: the discovery of less-is-more effects; the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; an advancement from vague labels to computational models of heuristics; the (...) development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an “adaptive toolbox;” and the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people’s adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. (shrink)