Abstract
This paper approaches the problem of testimony from a new direction. Rather than focusing on the epistemic grounds for testimony, it considers the problem from the perspective of an individual who must choose whom to trust from a population of many would-be testifiers. A computer simulation is presented which illustrates that in many plausible situations, those who trust without attempting to judge the reliability of testifiers outperform those who attempt to seek out the more reliable members of the community. In so doing, it presents a novel defense for the credulist position that argues one should trust testimony without considering the underlying reliability of the testifier.
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Notes
In their papers on testimony, Burge (1995), Hinchman (2005), and others make a distinction between one having a justification for p and one being entitled to believe that p. This distinction is not critical for this paper, and I will use “justification” broadly to encompass any type of epistemic entitlement to come to believe p.
In the simulations presented here, there are 1,500 propositions and individuals begin life with non-abstention beliefs about 15 of them.
Formally, each individual is assigned a reliability by performing an independent draw from a beta distribution with parameters α = 1.5 and β = 1.
This means that in this model there is no “belief revision.” This is certainly an idealization, which has been made for two reasons. First, following the literature on testimony this model focuses primarily on the acquisition of new beliefs not on belief revision. The later issue, called peer disagreement, has an extensive literature which will not be addressed here. Second, there is no uncontroversial way to model belief revision especially in the context of qualitative beliefs. Important future work should tackle this question directly to determine how robust the findings are to modifications of this assumption.
Kitcher (1993, chapt. 8) calls this “direct calibration” in contrast to “indirect calibration” where one relies on another to judge an individual’s reliability. For the purposes of this model subjective calibration is achieved in the following way. Each individual assigns every other individual an “agreement score” which is the number of propositions they both believe plus the number of propositions that they both disbelieve minus the number of propositions that one believes and the other disbelieves. The subjective reductionist then seeks out those who are highest according to this score.
Kadane and Lichtenstein (1982) discuss this issue within the context of a Bayesian model of belief. They prove that any consistent Bayesian must regard themselves as well calibrated. This way of modeling subjective calibration stands in contrast to other approaches (cf. Lehrer and Wagner 1981) which posit that individuals have second-order reliabilities—that they have some intrinsic ability to recognize the reliability of another individual. It is beyond the scope of this paper to engage in a philosophical debate about this methodology. But, it strikes me as strange to suppose that it normatively permissible that (a) Carlos believes that Jake is very reliable about some domain, (b) for most propositions p in this domain, Carlos knows that he and Jake disagree about the truth of p, and (c) Carlos refuses to change his mind about any of these propositions or about his view of Jake’s reliability. In the context of qualitative belief it might be possible to maintain this attitude in settings similar to the lottery paradox.
All data and simulation code will be available as electronic supplementary material.
Pritchard (2004) argues that Fricker’s (1995) version of reductionism allows for circular justification of many beliefs acquired via testimony. Beyond the philosophical concern with circularity, these simulation results illustrate that this can have significant negative effects for certain people in an epistemic community.
Simulations considered heterogeneous populations made up of individuals who could only solicit two others for testimony.
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Acknowledgments
The author would like to thank an anonymous reviewer and audiences in Pittsburgh, Groningen, Munich, and Düsseldorf for helpful comments. This research was supported by National Science Foundation grants SES 1026586 and SES 1254291.
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Zollman, K.J.S. Modeling the social consequences of testimonial norms. Philos Stud 172, 2371–2383 (2015). https://doi.org/10.1007/s11098-014-0416-7
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DOI: https://doi.org/10.1007/s11098-014-0416-7