One hundred and three participants solved conflict and non-conflict versions of four reasoning tasks using a two-response procedure: a base rate task, a causal reasoning task, a denominator neglect task, and a categorical syllogisms task. Participants were asked to give their first, intuitive answer, to make a Feeling of Rightness judgment, and then were given as much time as needed to rethink their answer. They also completed a standardized measure of IQ and the actively open-minded thinking questionnaire. The FORs of (...) both high- and low-capacity reasoners were responsive to conflict, such that FORs were lower for conflict relative to non-conflict problems. Consistent with the quantity hypothesis, high-capacity reasoners made a greater distinction between conflict and non-conflict items on measures of Type 2 thinking, namely, rethinking time and probability of changing answers. In contrast to the quality hypothesis, however, this rethinking time did not advantage the ability of the high-capacity group to produce normative answers, except for the base rate task. Indeed, we observed that the correlation between capacity and the probability of normative answers emerged at the initial response, rather than after rethinking. (shrink)

Mercier & Sperber (M&S) claim that the phenomenon of belief bias provides fundamental support for their argumentative theory and its basis in intuitive judgement. We propose that chronometric evidence necessitates a more nuanced account of belief bias that is not readily captured by argumentative theory.

Normative theories can be useful in developing descriptive theories, as when normative subjective expected utility theory is used to develop descriptive rational choice theory and behavioral game theory. “Ought” questions are also the essence of theories of moral reasoning, a domain of higher mental processing that could not survive without normative considerations.

We applaud many aspects of Elqayam & Evans' (E&E's) call for a descriptivist research programme in studying reasoning. Nevertheless, we contend that normative benchmarks are vital for understanding individual differences in performance. We argue that the presence of normative responses to particular problems by certain individuals should inspire researchers to look for converging evidence for analytic processing that may have a normative basis.

Mercier and Sperber (M&S) sketch a bleak picture of logical reasoning in classic, nonargumentative tasks. I argue that recent processing data indicate that despite people's poor performance they at least seek to adhere to traditional logical norms in these tasks. This implies that classic reasoning tasks are less artificialthan M&S's framework suggests.

Mercier & Sperber (M&S) argue for their argumentative theory in terms of communicative abilities. Insights can be gained by extending the discussion beyond human reasoning to rodent and robot navigation. The selection of arguments and conclusions that are mutually reinforcing can be cast as a form of abductive reasoning that I argue underlies the construction of cognitive maps in navigation tasks.

(2013). Matching bias in syllogistic reasoning: Evidence for a dual-process account from response times and confidence ratings. Thinking & Reasoning: Vol. 19, No. 1, pp. 54-77. doi: 10.1080/13546783.2012.735622.

A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining its likelihood of retrieval and therefore its effect on the reasoning process. This theory explores two main influences of belief on the activation levels of these (...) conclusions. First, believable conclusions have higher activation levels and so are more likely to be recalled during the evaluation of reasoning problems than unbelievable conclusions, and therefore, they have a greater influence on the reasoning process. Secondly, prior beliefs about the conclusion have a base level of activation and may be retrieved when logically irrelevant, influencing the evaluation of the problem. The theory of activation and memory is derived from the Atomic Components of Thought-Rational (ACT-R) cognitive architecture and so this account is formalized in an ACT-R cognitive model. Two experiments were conducted to test predictions of this model. Experiment 1 tested strength of belief and Experiment 2 tested the impact of a concurrent working memory load. Both of these manipulations increased the main effect of belief overall and in particular raised belief-based responding in indeterminately invalid problems. These effects support the idea that the activation level of conclusions formed during reasoning influences belief bias. This theory adds to current explanations of belief bias by providing a detailed specification of the role of working memory and how it is influenced by prior knowledge. (shrink)

In two experiments we tested the hypothesis that the mechanisms that produce belief bias generalise across reasoning tasks. In formal reasoning (i.e., syllogisms) judgements of validity are influenced by actual validity, believability of the conclusions, and an interaction between the two. Although apparently analogous effects of belief and argument strength have been observed in informal reasoning, the design of those studies does not permit an analysis of the interaction effect. In the present studies we redesigned two informal reasoning tasks: the (...) Argument Evaluation Task (AET) and a Law of Large Numbers (LLN) task in order to test the similarity of the phenomena concerned. Our findings provide little support for the idea that belief bias on formal and informal reasoning is a unitary phenomenon. First, there was no correlation across individuals in the extent of belief bias shown on the three tasks. Second, evidence for belief by strength interaction was observed only on AET and under conditions not required for the comparable finding on syllogistic reasoning. Finally, we found that while conclusion believability strongly influenced assessments of arguments strength, it had a relatively weak influence on the verbal justifications offered on the two informal reasoning tasks. (shrink)

Short abstract (98 words). Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given humans’ exceptional dependence on communication and vulnerability to misinformation. A wide range of (...) evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis. (shrink)

Severity of Test (SoT) is an alternative to Popper's logical falsification that solves a number of problems of the logical view. It was presented by Popper himself in 1963. SoT is a less sophisticated probabilistic model of hypothesis testing than Oaksford & Chater's (O&C's) information gain model, but it has a number of striking similarities. Moreover, it captures the intuition of everyday hypothesis testing.

Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is (...) a residual role for logic in understanding reasoning; and others put forward alternative formalisms for uncertain reasoning, or raise specific technical, methodological, or empirical challenges. In responding to these points, we aim to clarify the scope and limits of probability and logic in cognitive science; explore the meaning of the explanation of cognition; and re-evaluate the empirical case for Bayesian rationality. (shrink)

Oaksford & Chater (O&C) rely on a data fitting approach to show that a Bayesian model captures the core reasoning data better than its logicist rivals. The problem is that O&C's modeling has focused exclusively on response output data. I argue that this exclusive focus is biasing their conclusions. Recent studies that focused on the processes that resulted in the response selection are more positive for the role of logic.

A controversial claim in recent dual process accounts of reasoning is that intuitive processes not only lead to bias but are also sensitive to the logical status of an argument. The intuitive logic hypothesis draws upon evidence that reasoners take longer and are less confident on belief–logic conflict problems, irrespective of whether they give the correct logical response. In this paper, we examine conflict detection under conditions in which participants are asked to either judge the logical validity or believability of (...) a presented conclusion, accompanied by measures of eye movement and pupil dilation. The findings show an effect of conflict, under both types of instruction, on accuracy, latency, gaze shifts, and pupil dilation. Importantly, these effects extend to conflict trials in which participants give a belief‐based response (incorrectly under logic instructions or correctly under belief instructions) demonstrating both behavioral and physiological evidence in support of the logical intuition hypothesis. (shrink)

The belief bias in reasoning occurs when individuals are more willing to accept conclusions that are consistent with their beliefs than conclusions that are inconsistent. The present study...

The article develops and justifies, on the basis of the epistemological argumentation theory, two central pieces of the theory of evaluative argumentation interpretation: 1. criteria for recognizing argument types and 2. rules for adding reasons to create ideal arguments. Ad 1: The criteria for identifying argument types are a selection of essential elements from the definitions of the respective argument types. Ad 2: After presenting the general principles for adding reasons (benevolence, authenticity, immanence, optimization), heuristics are proposed for finding missing (...) reasons, for deductive arguments, e.g., semantic tableaux are suggested. (shrink)