This article seeks, first, to show that much of the existing normative work on argument from expert opinion (AEO) is problematic for failing to be properly informed by empirical findings on expert performance. Second, it seeks to show how, with the analytic tool of Bayesian reasoning, the problem diagnosed can be remedied to circumvent some of the problems facing the scheme-based treatment of AEOs. To establish the first contention, we will illustrate how empirical studies on factors conditioning expert reliability can (...) be drawn upon to re-construct. Walton’s critical questions matching the scheme of AEOs. To establish the second contention, we will illustrate how Walton’s re-constructed set of critical questions can be formalized within a Bayesian network. Finally, we will highlight how the specific ways in which the Bayesian framework we propose is both continuous with and distinct from the models of source reliability put forward by theorists like Bovens and Hartmann (2003). (shrink)

The paper introduces, compares and contrasts formal models of source reliability proposed in the epistemology literature, in particular the prominent models of Bovens and Hartmann and Olsson :127–143, 2011). All are Bayesian models seeking to provide normative guidance, yet they differ subtly in assumptions and resulting behavior. Models are evaluated both on conceptual grounds and through simulations, and the relationship between models is clarified. The simulations both show surprising similarities and highlight relevant differences between these models. Most importantly, however, our (...) evaluations reveal that important normative concerns arguably remain unresolved. The philosophical implications of this for testimony are discussed. (shrink)

Public support for responses to the coronavirus pandemic has sharply diverged on partisan lines in many countries, with conservatives tending to oppose lockdowns, social distancing, mask mandates and vaccines, and liberals far more supportive. This polarization may arise from the way in which the attitudes of each side is echoed back to them, especially on social media. In this paper, I argue that echo chambers are not to blame for this polarization, even if they are causally responsible for it. They (...) are not to blame, because belief calibration in an echo chamber is a rational process; moreover, the epistemically constitutive properties of echo chambers are not optional for epistemically social animals like us. There is no special problem of echo chambers; rather, there is a problem of misleading evidence (especially higher-order evidence). Accordingly, we ought to respond to misinformation about COVID neither by attempting to dismantle echo chambers nor by attempting to make people more rational, but rather by attempting to supplant unreliable higher-order evidence with better evidence. (shrink)

Psychological studies show that the beliefs of two agents in a hypothesis can diverge even if both agents receive the same evidence. This phenomenon of belief polarisation is often explained by invoking biased assimilation of evidence, where the agents’ prior views about the hypothesis affect the way they process the evidence. We suggest, using a Bayesian model, that even if such influence is excluded, belief polarisation can still arise by another mechanism. This alternative mechanism involves differential weighting of the evidence (...) arising when agents have different initial views about the reliability of their sources of evidence. We provide a systematic exploration of the conditions for belief polarisation in Bayesian models which incorporate opinions about source reliability, and we discuss some implications of our findings for the psychological literature. (shrink)

In recent years, the receipt and the perception of information has changed in ways which have fueled fears about the fates of our democracies. However, real information on these possibilities or the direction of these changes does not exist. Into this gap, Hahn and colleagues bring the power of Condorcet's (1785) Jury Theorem to show that changes in our information networks have affected voter inter‐dependence so that it is likely that voters are now collectively more ignorant even if individual voter (...) competence remains unchanged. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 602-620, July 2022.

Conditionals pervade every aspect of our thinking, from the mundane and everyday such as ‘if you eat too much cheese, you will have nightmares’ to the most fundamental concerns as in ‘if global warming isn’t halted, sea levels will rise dramatically’. Many decades of research have focussed on the semantics of conditionals and how people reason from conditionals in everyday life. Here it has been rather overlooked how we come to such conditionals in the first place. In many cases, they (...) are learned through testimony: someone warns us about the ill-effects of cheese. Any full account of the conditional must consequently incorporate such learning. Here, we provide a new formal account of belief change in response to a testimonial conditional. (shrink)

Bayes nets are a powerful tool for researchers in statistics and artificial intelligence. This chapter demonstrates that they are also of much use for philosophers and psychologists interested in (Bayesian) rationality. To do so, we outline the general methodology of Bayes nets modeling in rationality research and illustrate it with several examples from the philosophy and psychology of reasoning and argumentation. Along the way, we discuss the normative foundations of Bayes nets modeling and address some of the methodological problems it (...) raises. (shrink)