The appeal to expert opinion is an argument form that uses the verdict of an expert to support a position or hypothesis. A previous scheme-based treatment of the argument form is formalized within a Bayesian network that is able to capture the critical aspects of the argument form, including the central considerations of the expert's expertise and trustworthiness. We propose this as an appropriate normative framework for the argument form, enabling the development and testing of quantitative predictions as to how (...) people evaluate this argument, suggesting that such an approach might be beneficial to argumentation research generally. We subsequently present two experiments as an example of the potential for future research in this vein, demonstrating that participants' quantitative ratings of the convincingness of a proposition that has been supported with an appeal to expert opinion were broadly consistent with the predictions of the Bayesian model. (shrink)

Argumentation is pervasive in everyday life. Understanding what makes a strong argument is therefore of both theoretical and practical interest. One factor that seems intuitively important to the strength of an argument is the reliability of the source providing it. Whilst traditional approaches to argument evaluation are silent on this issue, the Bayesian approach to argumentation (Hahn & Oaksford, 2007) is able to capture important aspects of source reliability. In particular, the Bayesian approach predicts that argument content and source reliability (...) should interact to determine argument strength. In this paper, we outline the approach and then demonstrate the importance of source reliability in two empirical studies. These experiments show the multiplicative relationship between the content and the source of the argument predicted by the Bayesian framework. (shrink)

Bayesian probability has recently been proposed as a normative theory of argumentation. In this article, we provide a Bayesian formalisation of the ad Hitlerum argument, as a special case of the ad hominem argument. Across three experiments, we demonstrate that people's evaluation of the argument is sensitive to probabilistic factors deemed relevant on a Bayesian formalisation. Moreover, we provide the first parameter-free quantitative evidence in favour of the Bayesian approach to argumentation. Quantitative Bayesian prescriptions were derived from participants' stated subjective (...) probabilities (Experiments 1 and 2), as well as from frequency information explicitly provided in the experiment (Experiment 3). Participants' stated evaluations of the convincingness of the argument were well matched to these prescriptions. (shrink)

Possible measures to mitigate climate change require global collective actions whose impacts will be felt by many, if not all. Implementing such actions requires successful communication of the reasons for them, and hence the underlying climate science, to a degree that far exceeds typical scientific issues which do not require large-scale societal response. Empirical studies have identified factors, such as the perceived level of consensus in scientific opinion and the perceived reliability of scientists, that can limit people's trust in science (...) communicators and their subsequent acceptance of climate change claims. Little consideration has been given, however, to recent formal results within philosophy concerning the relationship between truth, the reliability of evidence sources, the coherence of multiple pieces of evidence/testimonies, and the impact of independence between sources of evidence. This study draws on these results to evaluate exactly what has been established in the empirical literature about the factors that bias the public's reception of scientific communications about climate change. (shrink)

(2013). Rational argument, rational inference. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 21-35. doi: 10.1080/19462166.2012.689327.

Risk communicators often need to communicate probabilistic predictions. On occasion, an event with 10% likelihood will occur, or one with 90% likelihood will not – a probabilistically unexpected ou...

ABSTRACTIn everyday situations, people regularly receive information from large groups of people and from single experts. Although lay opinions and expert opinions have been studied extensively in isolation, the present study examined the relationship between the two by asking how many laypeople are needed to counter an expert opinion. A Bayesian formalisation allowed the prescription of this quantity. Participants were subsequently asked to assess how many laypeople are needed in different situations. The results demonstrate that people are sensitive to the (...) relevant factors identified for determining how many lay opinions are required to counteract a single expert opinion. People's assessments were fairly good in line with Bayesian predictions. (shrink)

In the absence of an objective contingency, psychological studies have shown that people nevertheless attribute outcomes to their own actions. Thus, by wrongly inferring control in chance situations people appear to hold false beliefs concerning their agency, and are said to succumb to an illusion of control (IoC). In the current article, we challenge traditional conceptualizations of the illusion by examining the thesis that the IoC reflects rational and adaptive decision making. Firstly, we propose that the IoC is a by-product (...) of a rational uncertain judgment (“the likelihood that I have control over a particular outcome”). We adopt a Bayesian perspective to demonstrate that, given their past experience, people should be prone to ascribing skill to chance outcomes in certain situations where objectively control does not exist. Moreover, existing empirical evidence from the IoC literature is shown to support such an account. Secondly, from a decision-theoretic perspective, in many consequential situations, underestimating the chance of controlling a situation carries more costs than overestimating that chance. Thus, situations will arise in which people will incorrectly assign control to events in which outcomes result from chance, but the attribution is based on rational processes. (shrink)