Changing your mind

Walsh, Clare R.; Johnson‐Laird, P. N.

doi:10.3758/mc.37.5.624

Cited by 19 publications

(12 citation statements)

References 17 publications

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“…Because these conjunctions were ranked as more probable than their individual constituent propositions, the assessments violated the probability calculus-they are an instance of the so-called "conjunction" fallacy in which a conjunction is considered as more probable than either of its constituents (93). Like other results (94), they are also contrary to a common view-going back to William James (95) -that we accommodate an inconsistent fact with a minimal change to our existing beliefs (92,96).…”

Section: Strategies In Reasoningcontrasting

confidence: 53%

Mental models and human reasoning

Johnson‐Laird

2010

Proc. Natl. Acad. Sci. U.S.A.

372

207

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To be rational is to be able to reason. Thirty years ago psychologists believed that human reasoning depended on formal rules of inference akin to those of a logical calculus. This hypothesis ran into difficulties, which led to an alternative view: reasoning depends on envisaging the possibilities consistent with the starting point-a perception of the world, a set of assertions, a memory, or some mixture of them. We construct mental models of each distinct possibility and derive a conclusion from them. The theory predicts systematic errors in our reasoning, and the evidence corroborates this prediction. Yet, our ability to use counterexamples to refute invalid inferences provides a foundation for rationality. On this account, reasoning is a simulation of the world fleshed out with our knowledge, not a formal rearrangement of the logical skeletons of sentences.H uman beings are rational-a view often attributed to Aristotle-and a major component of rationality is the ability to reason (1). A task for cognitive scientists is accordingly to analyze what inferences are rational, how mental processes make these inferences, and how these processes are implemented in the brain. Scientific attempts to answer these questions go back to the origins of experimental psychology in the 19th century. Since then, cognitive scientists have established three robust facts about human reasoning. First, individuals with no training in logic are able to make logical deductions, and they can do so about materials remote from daily life. Indeed, many people enjoy pure deduction, as shown by the world-wide popularity of Sudoku problems (2). Second, large differences in the ability to reason occur from one individual to another, and they correlate with measures of academic achievement, serving as proxies for measures of intelligence (3). Third, almost all sorts of reasoning, from 2D spatial inferences (4) to reasoning based on sentential connectives, such as if and or, are computationally intractable (5). As the number of distinct elementary propositions in inferences increases, reasoning soon demands a processing capacity exceeding any finite computational device, no matter how large, including the human brain.

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Section: Strategies In Reasoningcontrasting

confidence: 53%

Mental models and human reasoning

Johnson‐Laird

2010

Proc. Natl. Acad. Sci. U.S.A.

372

207

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“…Likewise, participants tended to select such explanations as the most probable (in Experiment 1), to evaluate them as having the highest rank of probability (Experiment 2), and to assign them the highest probability (Experiment 3). These studies corroborate the finding that people are prepared to make nonminimal changes to resolve inconsistencies (Dieussaert et al, 2000;Elio & Pelletier, 1997;Politzer & Carles, 2001;Walsh & Johnson-Laird, 2009). The studies also supported the explanatory hypothesis: The principal goal that most individuals have in resolving an inconsistency is to explain its origins.…”

Section: Discussionsupporting

confidence: 87%

“…The next three experiments bore out the results of the pilot study. Its results also corroborated the preference for the refutation of generalizations rather than the refutations of categorical assertions-a result that is contrary to minimalism but that has been observed many times (Elio & Pelletier, 1997;Dieussaert et al, 2000;Politzer & Carles, 2001;Walsh & Johnson-Laird, 2009). …”

Section: %supporting

confidence: 87%

“…What we can say, however, is that a simple rejection of a categorical premise in our studies does not call for any change to tacit beliefs whatsoever. Hence, even the appeal to background beliefs does not save minimalism (for additional evidence against this appeal, see Walsh & Johnson-Laird, 2009). Of course, our results leave open the possibility that minimalism is a normative theory (see Harman, 1986, p. 7), in which case, they show that untrained individuals depart from a canon of rationality.…”

Section: Discussionmentioning

confidence: 97%

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The Need to Explain

Khemlani

Johnson‐Laird

2011

Quarterly Journal of Experimental Psychology

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How do reasoners deal with inconsistencies? James (1907) believed that the rational solution is to revise your beliefs and to do so in a minimal way. We propose an alternative: You explain the origins of an inconsistency, which has the side effect of a revision to your beliefs. This hypothesis predicts that individuals should spontaneously create explanations of inconsistencies rather than refute one of the assertions and that they should rate explanations as more probable than refutations. A pilot study showed that participants spontaneously explain inconsistencies when they are asked what follows from inconsistent premises. In three subsequent experiments, participants were asked to compare explanations of inconsistencies against minimal refutations of the inconsistent premises. In Experiment 1, participants chose which conclusion was most probable; in Experiment 2 they rank ordered the conclusions based on their probability; and in Experiment 3 they estimated the mean probability of the conclusions' occurrence. In all three studies, participants rated explanations as more probable than refutations. The results imply that individuals create explanations to resolve an inconsistency and that these explanations lead to changes in belief. Changes in belief are therefore of secondary importance to the primary goal of explanation.

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“…Hence, contrary to many philosophical accounts (following [66]), individuals do not always accommodate an inconsistent fact with a minimal change to their beliefs [67]. Instead, they simulate what might have happened, generating a mental model (or models) of the situation that explain the inconsistency [65], and they rate such explanations as more probable than minimal changes [68].…”

Section: Feature Reviewmentioning

confidence: 96%