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)

Norms—that is, specifications of what we ought to do—play a critical role in the study of informal argumentation, as they do in studies of judgment, decision-making and reasoning more generally. Specifically, they guide a recurring theme: are people rational? Though rules and standards have been central to the study of reasoning, and behavior more generally, there has been little discussion within psychology about why (or indeed if) they should be considered normative despite the considerable philosophical literature that bears on this (...) topic. In the current paper, we ask what makes something a norm, with consideration both of norms in general and a specific example: norms for informal argumentation. We conclude that it is both possible and desirable to invoke norms for rational argument, and that a Bayesian approach provides solid normative principles with which to do so. (shrink)

Much of what we believe we know, we know through the testimony of others. While there has been long-standing evidence that people are sensitive to the characteristics of the sources of testimony, for example in the context of persuasion, researchers have only recently begun to explore the wider implications of source reliability considerations for the nature of our beliefs. Likewise, much remains to be established concerning what factors influence source reliability. In this paper, we examine, both theoretically and empirically, the (...) implications of using message content as a cue to source reliability. We present a set of experiments examining the relationship between source information and message content in people's responses to simple communications. The results show that people spontaneously revise their beliefs in the reliability of the source on the basis of the expectedness of a source's claim and, conversely, adjust message impact by perceived reliability; hence source reliability and message content have a bi-directional relationship. The implications are discussed for a variety of psychological, philosophical and political issues such as belief polarization and dual-route models of persuasion. (shrink)

There has been much interest in group judgment and the so-called 'wisdom of crowds'. In many real world contexts, members of groups not only share a dependence on external sources of information, but they also communicate with one another, thus introducing correlations among their responses that can diminish collective accuracy. This has long been known, but it has-to date-not been examined to what extent different kinds of communication networks may give rise to systematically different effects on accuracy. We argue that (...) equations that relate group accuracy, individual accuracy, and group diversity are useful theoretical tools for understanding group performance in the context of research on group structure. In particular, these equations may serve to identify the kind of group structures that improve individual accuracy without thereby excessively diminishing diversity so that the net positive effect is an improvement even on the level of collective accuracy. Two experiments are reported where two structures are investigated from this perspective. It is demonstrated that the more constrained network outperforms the network with a free flow of information. (shrink)

Information generally comes from less than fully reliable sources. Rationality, it seems, requires that one take source reliability into account when reasoning on the basis of such information. Recently, Bovens and Hartmann (2003) proposed an account of the conjunction fallacy based on this idea. They show that, when statements in conjunction fallacy scenarios are perceived as coming from such sources, probability theory prescribes that the “fallacy” be committed in certain situations. Here, the empirical validity of their model was assessed. The (...) model predicts that statements added to standard conjunction problems will change the incidence of the fallacy. It also predicts that statements from reliable sources should yield an increase in fallacy rates (relative to unreliable sources). Neither the former (Experiment 1) nor the latter prediction (Experiment 3) was confirmed, although Experiment 2 showed that people can derive source reliability estimates from the likelihood of statements in a manner consistent with the tested model. In line with the experimental results, model fits and sensitivity analyses also provided very little evidence in favor of the model. This suggests that Bovens and Hartmann’s present model fails to explain fully people’s judgements in standard conjunction fallacy tasks. (shrink)

This paper explores ‘reasonable doubt’ as an enlightening notion to think of reasoning and decision-making generally, beyond the judicial domain. The paper starts from a decision-theoretic understanding of the notion, whereby it can be defined in terms of degrees of belief and a probabilistic confirmation threshold for action. It then highlights some of the limits of this notion, and proposes a richer analysis of epistemic states and reasoning through the lens of ‘reasonable doubt’, which in turn is likely to supplement (...) the DT framework. The strategy consists in fighting on two fronts: with DT, the paper claims that there is no absolute notion of ‘reasonable doubt’ but, pace DT, it shows that reasonable doubt cannot be accounted for only in terms of degrees of belief and probabilistic threshold. We argue that the lens of reasonable doubt sheds light on aspects of belief dynamics, as well as of the nature of epistemic attitudes, which are often obscured by belief-centred approaches. In particular, when it comes to acknowledging the necessary ignorance and irreducible uncertainty that we face in our everyday-life decisions, studying the various facets of doubt rather than focusing on what can be believed, enables one to do justice to the richness and diversity of the mental states in play. (shrink)

In this paper, it is argued that the most fruitful approach to developing normative models of argument quality is one that combines the argumentation scheme approach with Bayesian argumentation. Three sample argumentation schemes from the literature are discussed: the argument from sign, the argument from expert opinion, and the appeal to popular opinion. Limitations of the scheme-based treatment of these argument forms are identified and it is shown how a Bayesian perspective may help to overcome these. At the same time, (...) the contributions of the standard scheme-based approach are highlighted, and it is argued that only a combination of the insights of different traditions will yield a complete normative theory of argument quality. (shrink)

Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a (...) true opinion following group deliberation. The model incorporates a fine-grained and realistic representation of belief and trust, and it allows agents to consult outside information sources. We study a wide range of network structures and provide a detailed statistical analysis concerning the exact contribution of various network metrics to collective competence. Our results highlight and explain the collective risks involved in an overly networked or partitioned society. Specifically, we find that 96% of the variation in collective competence across networks can be attributed to differences in amount of connectivity and clustering, which are negatively correlated with collective competence. A study of bandwagon or “group think” effects indicates that both connectivity and clustering increase the probability that the network, wholly or partly, locks into a false opinion. Our work is interestingly related to Gerhard Schurz’s work on meta-induction and can be seen as broadly addressing a practical limitation of his approach. (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)

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)

We examine in detail three classic reasoning fallacies, that is, supposedly ``incorrect'' forms of argument. These are the so-called argumentam ad ignorantiam, the circular argument or petitio principii, and the slippery slope argument. In each case, the argument type is shown to match structurally arguments which are widely accepted. This suggests that it is not the form of the arguments as such that is problematic but rather something about the content of those examples with which they are typically justified. This (...) leads to a Bayesian reanalysis of these classic argument forms and a reformulation of the conditions under which they do or do not constitute legitimate forms of argumentation. (shrink)

In this paper, new evidence is presented for the assumption that the reason-relation reading of indicative conditionals ('if A, then C') reflects a conventional implicature. In four experiments, it is investigated whether relevance effects found for the probability assessment of indicative conditionals (Skovgaard-Olsen, Singmann, and Klauer, 2016a) can be classified as being produced by a) a conversational implicature, b) a (probabilistic) presupposition failure, or c) a conventional implicature. After considering several alternative hypotheses and the accumulating evidence from other studies as (...) well, we conclude that the evidence is most consistent with the Relevance Effect being the outcome of a conventional implicature. This finding indicates that the reason-relation reading is part of the semantic content of indicative conditionals, albeit not part of their primary truth-conditional content. (shrink)

Although argumentation plays an essential role in our lives, there is no integrated area of research on the psychology of argumentation. Instead research on argumentation is conducted in a number of separate research communities that are spread across disciplines and have only limited interaction. With a view to bridging these different strands, we first distinguish between three meanings of the word ?argument?: argument as a reason, argument as a structured sequence of reasons and claims, and argument as a social exchange. (...) All three meanings are integral to a complete understanding of human reasoning and cognition. Cognitive psychological research on argumentation has focused mostly on the first and second of these meanings, so we present perspectives on argumentation from outside of cognitive psychology, which focus on the second and third. Specifically, we give anoverview of the methods, goals, and disciplinary backgrounds of research on the production, the analysis, and the evaluation of arguments. Finally, inintroducing the experimental studies included in this special issue, which were conducted by researchers from a range of theoretical backgrounds, weunderline the breadth of argumentation research as well as stress opportunities for mutual awareness and integration. (shrink)

Informatics and the Foundations of Legal Reasoning represents a close collaboration between a wide range of disciplines and countries. Fourteen papers, together with a long analytical introduction by the editors, were selected from the contributions of legal theorists, computer scientists, philosophers and logicians who were members of an International Working Group supported by the European Commission. The Group was mandated to work towards determining how far the law is amenable to formal modeling, and in what ways computers might assist legal (...) thinking and practice. The book is the result of discussions held by the Group over two and half years. It will help students and researchers from different backgrounds to focus on a common set of topics of increasing general interest. It embodies the results of work in progress and suggests many issues for further discussion. A stimulating text for undergraduate and graduate courses in law, philosophy and computer science departments, as well as for those interested in the place of computers in legal practice, especially at the international level. (shrink)

This paper examines the basic question of how we can come to form accurate beliefs about the world when we do not fully know how good or bad our evidence is. Here, we show, using simulations with otherwise optimal agents, the cost of misjudging the quality of our evidence. We compare different strategies for correctly estimating that quality, such as outcome‐ and expectation‐based updating. We also identify conditions under which misjudgment of evidence quality can nevertheless lead to accurate beliefs, as (...) well as those conditions where no strategy will help. These results indicate both where people will nevertheless succeed and where they will fail when information quality is degraded. (shrink)

The notion of “the burden of proof” plays an important role in real-world argumentation contexts, in particular in law. It has also been given a central role in normative accounts of argumentation, and has been used to explain a range of classic argumentation fallacies. We argue that in law the goal is to make practical decisions whereas in critical discussion the goal is frequently simply to increase or decrease degree of belief in a proposition. In the latter case, it is (...) not necessarily important whether that degree of belief exceeds a particular threshold (e.g., ‘reasonable doubt’). We explore the consequences of this distinction for the role that the “burden of proof” has played in argumentation and in theories of fallacy. (shrink)

As argumentation theory has moved away from classical logic as a standard, sources have played an increasingly important role in the psychology of argumentation. Considering the connections between arguments and their sources is important for both descriptive and normative projects. This chapter draws together different strands of research in the psychology of argumentation and their differing views on source characteristics: namely, procedural rules, pragmatics, argumentation schemes and Bayesian Argumentation. We argue for a reconciliation of these different approaches around a probabilistic (...) notion of relevance. (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)

In a recent article in Argumentation, O’Keefe (Argumentation 21:151–163, 2007) observed that the well-known ‘framing effects’ in the social psychological literature on persuasion are akin to traditional fallacies of argumentation and reasoning and could be exploited for persuasive success in a way that conflicts with principles of responsible advocacy. Positively framed messages (“if you take aspirin, your heart will be more healthy”) differ in persuasive effect from negative frames (“if you do not take aspirin, your heart will be less healthy”), (...) despite containing ‘equivalent’ content. This poses a potential problem, because people might be unduly (and unsuspectingly) influenced by mere presentational differences. By drawing on recent cognitive psychological work on framing effects in choice and decision making paradigms, however, we show that establishing whether two arguments are substantively equivalent—and hence, whether there is any normative requirement for them to be equally persuasive—is a difficult task. Even arguments that are logically equivalent may not be information equivalent. The normative implications of this for both speakers and listeners are discussed. (shrink)

In this article, we argue for the general importance of normative theories of argument strength. We also provide some evidence based on our recent work on the fallacies as to why Bayesian probability might, in fact, be able to supply such an account. In the remainder of the article we discuss the general characteristics that make a specifically Bayesian approach desirable, and critically evaluate putative flaws of Bayesian probability that have been raised in the argumentation literature.

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

Van Gelder's specification of the dynamical hypothesis does not improve on previous notions. All three key attributes of dynamical systems apply to Turing machines and are hence too general. However, when a more restricted definition of a dynamical system is adopted, it becomes clear that the dynamical hypothesis is too underspecified to constitute an interesting cognitive claim.

In this chapter, we outline the range of argument forms involving causation that can be found in everyday discourse. We also survey empirical work concerned with the generation and evaluation of such arguments. This survey makes clear that there is presently no unified body of research concerned with causal argument. We highlight the benefits of a unified treatment both for those interested in causal cognition and those interested in argumentation, and identify the key challenges that must be met for a (...) full understanding of causal argumentation. (shrink)

Critical (necessary or sufficient) features in categorisation have a long history, but the empirical evidence makes their existence questionable. Nevertheless, there are some cases that suggest critical feature effects. The purpose of the present work is to offer some insight into why classification decisions might misleadingly appear as if they involve critical features. Utilising Tversky's (1977) contrast model of similarity, we suggest that when an object has a sparser representation, changing any of its features is more likely to lead to (...) a change in identity than it would in objects that have richer representations. Experiment 1 provides a basic test of this suggestion with artificial stimuli, whereby objects with a rich or a sparse representation were transformed by changing one of their features. As expected, we observed more identity judgements in the former case. Experiment 2 further confirms our hypothesis, with realistic stimuli, by assuming that superordinate categories have sparser representations than subordinate ones. These results offer some insight into the way feature changes may or may not lead to identity changes in classification decisions. (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.

The statistics of small samples are often quite different from those of large samples, and this needs to be taken into account in assessing the rationality of human behavior. Specifically, in evaluating human responses to environmental statistics, it is the effective environment that matters; that is, the environment actually experienced by the agent needs to be considered, not simply long‐run frequencies. Significant deviations from long‐run statistics may arise through experiential limitations of the agent that stem from resource constraints and/or information‐processing (...) bounds. The article draws together recent work from a number of areas in judgment and decision making ranging from randomness perception (Hahn & Warren, ), information sampling (Hertwig & Pleskac, ; Kareev et al., ), and consequences of choice for exploration or exploitation (e.g., Denrell, ) to demonstrate how proper consideration of these deviations leads to reevaluation of behaviors that are otherwise deemed irrational. (shrink)

One of the most striking features of is the detail with which behavior on logical reasoning tasks can now be predicted and explained. This detail is surprising, given the state of the field 10 to 15 years ago, and it has been brought about by a theoretical program that largely ignores consideration of cognitive processes, that is, any kind of internal behavior that generates overt responding. It seems that an increase in explanatory power can be achieved by restricting a psychological (...) theory. (shrink)

Concepts allow us to treat different objects equivalently according to shared attributes, and hence to communicate about, draw inferences from, reason with, and explain these objects. Understanding how concepts are formed and used is thus essential to understanding and applying these basic processes, and the topic of similarity-based classification is central to psychology, artificial intelligence, statistics, and philosophy. This book brings together leading researchers, reflecting the key topics and important developments in the field and provides a uniquely interdisciplinary overview of (...) the subject. (shrink)

: A popular belief is that the process whereby search engines tailor their search results to individual users, so-called personalization, leads to filter bubbles in the sense of ideologically segregated search results that would tend to reinforce the user’s prior view. Since filter bubbles are thought to be detrimental to society, there have been calls for further legal regulation of search engines beyond the so-called Right to be Forgotten Act. However, the scientific evidence for the filter bubble hypothesis is surprisingly (...) limited. Previous studies of personalization have focused on the extent to which different users get different results lists without taking the content on the webpages into account. Such methods are unsuitable for detecting filter bubbles as such. In this paper, we propose a methodology that takes content differences between webpages into account. In particular, the method involves studying the extent to which users with strong opposing views on an issue receive search results that are correlated content-wise with their personal view. Will users of with strong prior opinion that X is true on average have a larger share of search results that are in favor of X than users with a strong prior opinion that X is false? We illustrate our methodology at work, but also the non-trivial challenges it faces, by a small-scale study of the extent to which Google Search leads to ideological segregation on the issue of man-made climate change. (shrink)