Simplicity and probability in causal explanation

Lombrozo, Tania

doi:10.1016/j.cogpsych.2006.09.006

Cited by 300 publications

(368 citation statements)

References 45 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: 49%

Mental models and human reasoning

Johnson‐Laird

2010

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

356

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: 49%

Mental models and human reasoning

Johnson‐Laird

2010

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

356

207

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“…But Douven and Schupbach (2015a) found that, at least in some contexts, Bayes' rule is systematically violated because people's belief updates are influenced by explanatory considerations. These results did not come as a complete surprise, given that previous research had already shown that explanation plays a variety of roles in belief formation and in cognition more generally (Chi, de Leeuw, Chiu, and LaVancher 1994;Legare and Lombrozo 2014;Lombrozo 2006Lombrozo , 2007Lombrozo , 2012Pennington and Hastie 1992; for more recent results, see Walker, Lombrozo, Williams, Rafferty, and Gopnik 2016).…”

Section: Introductionmentioning

confidence: 84%

Explanation, updating, and accuracy

Douven¹

2016

Journal of Cognitive Psychology

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There is evidence that people update their credences partly on the basis of explanatory considerations. Philosophers have recently argued that to minimise the inaccuracy of their credences, people's updates also ought to be partly based on such considerations. However, there are many ways in which explanatory considerations can factor into updating, not all of which minimise inaccuracy. It is an open question whether in their updating, people take explanatory considerations into account in a way that philosophers would deem recommendable. To address this question, we re-analyse data from an experiment reported in Douven and Schupbach, "The role of explanatory considerations in updating" (Cognition, 2015). ARTICLE HISTORY

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“…Experiments by Lombrozo (2007) focus on a notion of simplicity formalized as number of causes cited by a hypothesis. Her research broaches two questions: First, is this formal idea recognized as an explanatory virtue in actual human reasoning (the similarity question)?…”

Section: Ed(eh|k)=pr(e|handk)-pr(e|k)mentioning

confidence: 99%

Experimental Philosophy Meets Formal Epistemology

Schupbach¹

2016

A Companion to Experimental Philosophy

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Simplicity and probability in causal explanation

Cited by 300 publications

References 45 publications

Mental models and human reasoning

Mental models and human reasoning

Explanation, updating, and accuracy

Experimental Philosophy Meets Formal Epistemology

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