Are people rational? This question was central to Greek thought and has been at the heart of psychology and philosophy for millennia. This book provides a radical and controversial reappraisal of conventional wisdom in the psychology of reasoning, proposing that the Western conception of the mind as a logical system is flawed at the very outset. It argues that cognition should be understood in terms of probability theory, the calculus of uncertain reasoning, rather than in terms of logic, the calculus (...) of certain reasoning. (shrink)

Dual process theories conceive human thinking as an interplay between heuristic processes that operate automatically and analytic processes that demand cognitive effort. The interaction between these two types of processes is poorly understood. De Neys and Glumicic (2008) recently found that most of the time heuristic processes are successfully monitored. This monitoring, however, would not demand as many cognitive resources as the analytic thinking that is needed to solve reasoning problems. In the present study we tested the crucial assumption about (...) the effortless nature of the monitoring process directly. Participants solved base-rate neglect problems in which heuristic and analytic processes cued a conflicting response or not. Half of the participants reasoned under a secondary task load. A surprise recall task was used as an implicit measure of whether the participants detected the conflict in the problems. Results showed that, even under load, base-rate recall performance was better for conflict problems than for no-conflict problems. Although participants made more reasoning errors under load, recall of the conflict problems was not affected by the working memory load. These findings support the claim about the successful and undemanding nature of the conflict detection process during thinking. (shrink)

As stated by Jean-Pierre Changeux (2004) in his last book, The Physiology of Truth , objective knowledge does exist, and our brains are naturally equipped to recognise it. The results presented here provide the first insights on (1) the cerebral basis of reasoning errors, and (2) the neurocognitive dynamics that lead the human brain towards logical truth. We propose to call this new approach “neuropedagogy of reasoning”.

In this paper, I show that the question of how dual process theories of reasoning and judgement account for conflict between System 1 (heuristic) and System 2 (analytic) processes needs to be explicated and addressed in future research work. I demonstrate that a simple additive probability model that describes such conflict can be mapped on to three different cognitive models. The pre-emptive conflict resolution model assumes that a decision is made at the outset as to whether a heuristic or analytic (...) process will control the response. The parallel-competitive model assumes that each system operates in parallel to deliver a putative response, resulting sometimes in conflict that then needs to be resolved. Finally, the default-interventionist model involves the cueing of default responses by the heuristic system that may or may not be altered by subsequent intervention of the analytic system. A second, independent issue also emerges from this discussion. The superior performance of higher-ability participants on reasoning tasks may be due to the fact that they engage in more analytic reasoning ( quantity hypothesis ) or alternatively to the fact that the analytic reasoning they apply is more effective ( quality hypothesis ). (shrink)

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we (...) explore fast and frugal heuristics – simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data – that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program. Key Words: adaptive toolbox; bounded rationality; decision making; elimination models; environment structure; heuristics; ignorance-based reasoning; limited information search; robustness; satisficing; simplicity. (shrink)

Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational (...) limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate. Key Words: biases; descriptive models; heuristics; individual differences; normative models; rationality; reasoning. (shrink)

Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking by (...) representativeness, and Ss erroneously predicted rare events and extreme values if these happened to be representative. The experience of unjustified confidence in predictions and the prevalence of fallacious intuitions concerning statistical regression are traced to the representativeness heuristic. (shrink)

Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve (...) complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. (shrink)

Without Good Reason offers a clear critical account of the debate in philosophy and cognitive science about whether humans are rational. Various experiments performed over the last several decades have been interpreted as showing that humans are irrational; certain philosophers, on the other hand, have argued that it is a conceptual truth that humans must be rational. Edward Stein concludes that the question of human rationality should be answered not conceptually but empirically: the resources of a fully developed cognitive science (...) need to be used not only to answer this question but generally in investigations of the nature of human knowledge and understanding. (shrink)

Two experiments examined the contribution of working memory (WM) to the retrieval and inhibition of background knowledge about counterexamples (alternatives and disablers, Cummins, ) during conditional reasoning. Experiment 1 presented a conditional reasoning task with everyday, causal conditionals to a group of people with high and low WM spans. High spans rejected the logically invalid AC and DA inferences to a greater extent than low spans, whereas low spans accepted the logically valid MP and MT inferences less frequently than high (...) spans. In Experiment 2, an executive-attention-demanding secondary task was imposed during the reasoning task. Findings corroborate that WM resources are used for retrieval of stored counterexamples and that people with high WM spans will use WM resources to inhibit the counterexample activation when the type of counterexample conflicts with the logical validity of the reasoning problem. (shrink)

Although deductive reasoning is a closed system, one's beliefs about the world can influence validity judgements. To understand the associated functional neuroanatomy of this belief-bias we studied 14 volunteers using event-related fMRI, as they performed reasoning tasks under neutral, facilitatory and inhibitory belief conditions. We found evidence for the engagement of a left temporal lobe system during belief-based reasoning and a bilateral parietal lobe system during belief-neutral reasoning. Activation of right lateral prefrontal cortex was evident when subjects inhibited a prepotent (...) response associated with belief-bias and correctly completed a logical task, a finding consistent with its putative role in cognitive monitoring. By contrast, when logical reasoning was overcome by belief-bias, there was engagement of ventral medial prefrontal cortex, a region implicated in affective processing. This latter involvement suggests that belief-bias effects in reasoning may be mediated through an influence of emotional processes on reasoning. (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.

Stanovich & West analyze individual differences with respect to response output (e.g., participants' numerical estimates). They do not analyze the underlying cognitive processes that led to the outputs; they thereby probably misclassify some non-normative responses as normative. Using base rate neglect and overconfidence as examples, I demonstrate the advantages of analyzing cognitive processes further.

Human reasoning is often biased by stereotypical intuitions. The nature of such bias is not clear. Some authors claim that people are mere heuristic thinkers and are not aware that cued stereotypes might be inappropriate. Other authors claim that people always detect the conflict between their stereotypical thinking and normative reasoning, but simply fail to inhibit stereotypical thinking. Hence, it is unclear whether heuristic bias should be attributed to a lack of conflict detection or a failure of inhibition. We introduce (...) a neuroscientific approach that bears on this issue. Participants answered a classic decision-making problem while the activation of brain regions believed to be involved in conflict detection and response inhibition was monitored. Results showed that although the inhibition area was specifically activated when stereotypical responses were avoided, the conflict-detection area was activated even when people reasoned stereotypically. The findings suggest that people detect their bias when they give intuitive responses. (shrink)