New paradigm psychology of reasoning

Over, David E.

doi:10.1080/13546780903266188

Cited by 123 publications

(105 citation statements)

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“…These results provide support for a broadly Bayesian approach to the psychology of reasoning (Elqayam & Over, 2013;Oaksford & Chater, 2001Over, 2009). …”

Section: Discussionsupporting

confidence: 48%

Discounting testimony with the argument ad hominem and a Bayesian congruent prior model.

Bhatia

Oaksford

2015

Journal of Experimental Psychology: Learning, Memory, and Cogni

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When directed to ignore evidence of a witness' previous bad character because of a violation of the rules of evidence, are jurors' beliefs still affected? The intuition is that they will be because in everyday argumentation, fallacies, like the ad hominem, are effective argumentative strategies. An ad hominem argument (against the person) undermines a conclusion by questioning the character of the proposer. This intuition divides current theories of argumentation. According to pragmadialectical theory (e.g., Van Eemeren & Grootendorst, 2004) procedural rules exactly like the rules of evidence are part of our cognitive resources for evaluating arguments. If one of these rules is violated, an argument should be treated as a fallacy and so it should not alter someone's belief in the conclusion.Some recent experiments investigating how reasonable these arguments are perceived to be seem to support this account (Van Eemeren, Garssen, & Meufells, 2009). These experiments are critiqued from the perspective of the relevance (Walton, 2008(Walton, , 2009) and epistemic (Hahn & Oaksford, 2006Oaksford & Hahn, 2004) approaches to argumentation. An experiment investigates the predictions of these approaches for a graded belief change version of Van Eemeren et al.'s (2009) experiment and the results are modelled using a Bayesian congruent prior model. These results cannot be explained by the pragmadialectical approach and show that in everyday argument people are extremely sensitive to the epistemic relevance of evidence. Moreover, it seems highly unlikely that this can be switched off in more formal contexts such as the courtroom. In the court room, many factors affect how persuasive jurors find the arguments put forward by counsel (Spellman & Schauer, 2012). The arguments presented in court are constrained by strict procedural rules about, for example, admissible evidence, not asking leading questions and so on. These procedural rules guarantee the quality of the arguments and evidence.However, lawyers occasionally violate these rules, intentionally or unintentionally, in order to influence the jury. For example, counsel may introduce evidence of a witness' previous bad character, e.g., media reports of drunkenness or wife abuse. In In the US, under the Federal Rules of Evidence (2014) this may be inadmissible as irrelevant hearsay but only if the opposing counsel objects will the judge rule on its admissibility. At this point, she can inform the jury that the rules of evidence have been violated and direct them to ignore the evidence.The goal of the arguments put forward in court is to bring about quantitative changes in jurors' degrees of belief, ultimately, in the guilt or innocence of the defendant. When the judge points out that an argument, e.g., the witness abused his wife, violates a rule of evidence does this affect jurors' degrees of belief in the conclusions they are asked to evaluate? Pointing out the violation is intended to remove any effect of the argument on jurors' degree of belief but once it has...

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“…These results provide support for a broadly Bayesian approach to the psychology of reasoning (Elqayam & Over, 2013;Oaksford & Chater, 2001Over, 2009). …”

Section: Discussionsupporting

confidence: 48%

Discounting testimony with the argument ad hominem and a Bayesian congruent prior model.

Bhatia

Oaksford

2015

Journal of Experimental Psychology: Learning, Memory, and Cogni

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“…Moreover, if System 2 reasoning cannot modify general knowledge in System 1, its purpose seems unclear. On the other hand, if birds fly is retracted from world knowledge, along with other defeasible generalizations, then almost all of general knowledge will be stripped away-as generalizations outside mathematics are typically defeasible (Oaksford & Chater, 2007, 2009)-leading System 1 into inferential paralysis. Oaksford and Chater (2012) argued that the best way to avoid these unpalatable conclusions and account for the defeasibility of human reasoning is to adopt the SFDP view in which representing birds fly in WM amounts to the assumption that the probability that something flies given it is a bird is very close to 1 (Pr(flies(x)|bird(x)) ≈ 1).…”

Section: Probabilistic Single Function Dual Process Theorymentioning

confidence: 99%

“…The new paradigm in reasoning (Manktelow, 2012;Over, 2009; and recent special issue of Thinking and Reasoning) is explicitly probabilistic. However, different theorists who fall under the "new paradigm," while in broad agreement, diverge on how probabilities figure in the psychology of human reasoning, For example, Pfeiffer andKleiter (2009, 2010;see also, Pfeifer, 2013) adopt a mental probability logic approach based on deduction and an interval based probabilistic semantics.…”

Section: The Probabilistic Approachmentioning

confidence: 99%

Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

Oaksford

Chater

2014

Thinking & Reasoning

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In this paper, it is argued that single function dual process theory is a more credible psychological account of non-monotonicity in human conditional reasoning than recent attempts to apply logic programming (LP) approaches in artificial intelligence to these data.LP is introduced and among other critiques, it is argued that it is psychologically unrealistic in a similar way to hash coding in the classicism vs connectionism debate. Second, it is argued that causal Bayes nets provide a framework for modelling probabilistic conditional inference in System 2 that can deal with patterns of inference LP cannot. Third, we offer some speculations on how the cognitive system may avoid problems for System 1 identified by Fodor in 1983. We conclude that while many problems remain, the probabilistic single function dual processing theory is to be preferred over LP as an account of the nonmonotonicity of human reasoning. Dual process theories (Evans 2003(Evans , 2007Evans & Stanovich, 2013;Kahneman, 2011;Sloman, 1996;Stanovich, 2011; Stanovich & West, 2000;Wason & Evans, 1975) invoke two separate cognitive systems to explain performance on a variety of cognitive tasks. These are labelled System 1 and System 2. System 1 is rapid, parallel, automatic, do not require the resources of working memory (WM), and only their final product is posted in consciousness.In contrast, System 2 is slow sequential, and analytic and makes use of the central working memory system. In particular, System 2 ''permits abstract hypothetical thinking that cannot be achieved by System 1' ' (Evans 2003, p. 454). Recently, Oaksford and Chater (2012) argued that accounting for non-monotonic or defeasible reasoning in dual process theory required that both System 2 WM representations and System 1 long term memory (LTM) representations need to be interpreted probabilistically. This position is consistent with Evans and Over (2004; see also Over, Evans, & Elqayam, 2010) adoption of probability logic (Adams, 1998) as underpinning analytic processes in System 2. But it contrasts with accounts which treat analytic processes in System 2 as underpinned by standard binary truth functional logic (Heit & Rotello, 2010;Klauer et al., 2010;Rips, 2001Rips, , 2002 Stanovich & West, 2000;Stanovich, 2011). Oaksford and Chater (2012) labelled the former approach, the single function dual process (SFDP) approach and the latter the dual function dual process (DFDP) approach. Our goal in this paper is to confront some further problems and challenges for the probabilistic SFDP approach but first we rehearse Oaksford and Chater's (2012) argument in detail. Probabilistic Single Function Dual Process TheoryBoth the dual process theory (Evans 2002) and the probabilistic approach (Oaksford and Chater 1991, 1998 developed out of a critique of the classical logicist approach to cognitive architecture (Fodor 1975;Pylyshyn 1984), which is a logical single 4 function dual process theory. The store of world knowledge in LTM consists of a consistent set of logical formulae i...

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“…Perceived complexity and randomness are also of the utmost importance within the "new paradigm psychology of reasoning" (Over, 2009). As an example, let us consider the representativeness heuristic (Tversky and Kahneman, 1974).…”

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confidence: 99%

Algorithmic complexity for psychology: a user-friendly implementation of the coding theorem method

et al. 2015

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Kolmogorov-Chaitin complexity has long been believed to be impossible to approximate when it comes to short sequences (e.g. of length 5-50). However, with the newly developed coding theorem method the complexity of strings of length 2-11 can now be numerically estimated. We present the theoretical basis of algorithmic complexity for short strings (ACSS) and describe an R-package providing functions based on ACSS that will cover psychologists' needs and improve upon previous methods in three ways: (1) ACSS is now available not only for binary strings, but for strings based on up to 9 different symbols, (2) ACSS no longer requires time-consuming computing, and (3) a new approach based on ACSS gives access to an estimation of the complexity of strings of any length. Finally, three illustrative examples show how these tools can be applied to psychology. Keywords Algorithmic complexity · Randomness · Subjective probability · Coding theorem method Randomness and complexity are two concepts which are intimately related and are both central to numerous recent developments in various fields, including finance (Taufemback et al., 2011, Brandouy et al., 2012, linguistics (Gruber, 2010;Naranan, 2011), neuropsychology (Machado et al., 2010;Fernández et al., 2011Fernández et al., , 2012, psychiatry (Yang and Tsai, 2012;Takahashi 2013), genetics (Yagil, 2009;Ryabko et al. 2013), sociology (Elzinga, 2010 and the behavioral sciences (Watanabe et al., 2003;Scafetta et al., 2009). In psychology, randomness and complexity have recently attracted interest, following the realization that they could shed light on a diversity of previously undeciphered behaviors and mental processes. It has been found, for instance, that the subjective difficulty of a concept is directly related to its "boolean complexity", defined as the shortest logical description of a concept (Feldman, 2000(Feldman, , 2003(Feldman, , 2006. In the same vein, visual detection of shapes has been shown to be related to contour complexity (Wilder et al., 2011).More generally, perceptual organization itself has been described as based on simplicity or, equivalently, likelihood (Chater, 1996;Chater and Vitányi, 2003), in a model reconciling the complexity approach (perception is organized to minimize complexity) and a probability approach (perception is organized to maximize likelihood), very much in line with our view in this paper. Even the perception of similarity may be viewed through the lens of (conditional) complexity (Hahn et al., 2003).Randomness and complexity also play an important role in modern approaches to selecting the "best" among a set of candidate models (i.e., model selection; e.g., Myung et Behav Res (2016) 48:314-329 315 al., 2006Kellen et al., 2013), as discussed in more detail below in the section called "Relationship to complexity based model selection".Complexity can also shed light on short term memory storage and recall, more specifically, on the process underlying chunking. It is well known that the short term memory span lies b...

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New paradigm psychology of reasoning

Cited by 123 publications

References 12 publications

Discounting testimony with the argument ad hominem and a Bayesian congruent prior model.

Discounting testimony with the argument ad hominem and a Bayesian congruent prior model.

Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

Algorithmic complexity for psychology: a user-friendly implementation of the coding theorem method

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