Temporal delays can facilitate causal attribution: Towards a general timeframe bias in causal induction

Does reasoning occur on the Wason selection task, or are card selections determined purely on the basis of heuristic processes? To answer this question two relevance-based theories of reasoning are compared: (1) the theory of Evans (1984, 1989; Evans &; Over, 1996), which takes the heuristic viewpoint, and (2) the theory of Sperber, Cara, and Girotto (1995), which takes the reasoning viewpoint. In three experiments, the effect of removing matching cards from the selection task array is examined. It is argued that the Sperber et al. theory makes clearer predictions about the results of these manipulations, which are confirmed, and that the Evans theory can only accommodate them if it allows the operation of reasoning processes. The results are also discussed in relation to Roth's (1979) account of the selection task, mental models theory, and information gain theory.     

Dual-process theories of reasoning: The test of development

Dual-process theories have become increasingly influential in the psychology of reasoning. Though the distinction they introduced between intuitive and reflective thinking should have strong developmental implications, the developmental approach has rarely been used to refine or test these theories. In this article, I review several contemporary dual-process accounts of conditional reasoning that theorize the distinction between the two systems of reasoning as a contrast between heuristic and analytic processes, probabilistic and mental model reasoning, or emphasize the role of metacognitive processes in reflective reasoning. These theories are evaluated in the light of the main developmental findings. It is argued that a proper account of developmental phenomena requires the integration of the main strengths of these three approaches. I propose such an integrative theory of conditional understanding and argue that the modern dual-process framework could benefit from earlier contributions that made the same distinction between intuition and reflective thinking, such as Piaget’s theory.     

归纳推理和演绎推理的关系理论及其模型

推理是人类高级认知过程的一种,相关的心理学研究一般将其分为归纳推理和演绎推理两个方面。归纳推理是从特殊到一般的推理过程,与之相对的演绎推理则是从一般到特殊的过程。归纳推理和演绎推理的关系问题是当前心理推理研究领域的一个重点问题。这一问题主要有两种理论解释：一种是单过程理论,该理论认为归纳推理和演绎推理本质上是同一个认知过程,以单过程理论为基础构建的推理模型称为单维模型;另一种是双过程理论,认为归纳推理和演绎推理是两个不同的认知过程,并不同程度地受到启发和分析过程的影响。未来研究可多关注推理的时间进程,以及采用不同的研究方法对各自理论提供数据支持。     

Children's Reasoning in Solving Relational Problems of Deduction

This article reports on a study of children's deductive reasoning in solving novel relational problems. Detailed protocols were obtained from 264 children (aged 9- 12 years) who verbalised their thinking as they solved the problems. The study included the development of a three-phase theory based on Johnson-Laird and Byrne's mental models perspective, but with some distinct modifications. These include a focus on the relational complexity entailed in model construction and in premise integration, and the advancement of four reasoning principles that are applied throughout problem solution (in contrast to Johnson-Laird's falsification processes as the hallmark of deductive reasoning). The reported case studies and the results of statistical analyses supported predictions arising from the proposed theory, including the key role of the reasoning principles. The results also showed that problem difficulty is a function of relational complexity, not of the number of models to be constructed, as argued by Johnson-Laird and Byrne.     

A dual-process specification of causal conditional reasoning

There are two accounts describing causal conditional reasoning: the probabilistic and the mental models account. According to the probabilistic account, the tendency to accept a conclusion is related to the probability by which cause and effect covary. According to the mental models account, the tendency to accept a conclusion relates to the availability of counterexamples. These two accounts are brought together in a dual-process theory: It is argued that the probabilistic reasoning process can be considered as a heuristic process whereas the mental models account can be seen as its analytic counterpart. Experiment 1 showed that the two processes differ on a temporal dimension: The variation in fast responses was best predicted by the variation in likelihood information, while the variation in slow responses was best predicted by variation in counterexample information. Experiments 2 and 3 validate the override principle: The likelihood conclusion can be overwritten when specific counterexamples are retrieved in time. In Experiment 2 both accounts were compared based on their difference in input. In Experiment 3 we used a verbal protocol analysis to validate the dual-process idea at the output level. The data of the three experiments provide converging support for framing the two reasoning accounts in a dual-process theory.     

A relevance theory of induction

A framework theory, organized around the principle of relevance, is proposed for category-based reasoning. According to the relevance principle, people assume that premises are informative with respect to conclusions. This idea leads to the prediction that people will use causal scenarios and property reinforcement strategies in inductive reasoning. These predictions are contrasted with both existing models and normative logic. Judgments of argument strength were gathered in three different countries, and the results showed the importance of both causal scenarios and property reinforcement in categorybased inferences. The relation between the relevance framework and existing models of category-based inductive reasoning is discussed in the light of these findings.     

Heuristic thinking and human intelligence: a commentary on Marewski,Gaissmaier and Gigerenzer

Marewski, Gaissmaier and Gigerenzer (2009) present a review of research on fast and frugal heuristics, arguing that complex problems are best solved by simple heuristics, rather than the application of knowledge and logical reasoning. We argue that the case for such heuristics is overrated. First, we point out that heuristics can often lead to biases as well as effective responding. Second, we show that the application of logical reasoning can be both necessary and relatively simple. Finally, we argue that the evidence for a logical reasoning system that co-exists with simpler heuristic forms of thinking is overwhelming. Not only is it implausible a priori that we would have evolved such a system that is of no use to us, but extensive evidence from the literature on dual processing in reasoning and judgement shows that many problems can only be solved when this form of reasoning is used to inhibit and override heuristic thinking.     

No interpretation without representation: the role of domain-specific representations and inferences in the Wason selection task

The Wason selection task is a tool used to study reasoning about conditional rules. Performance on this task changes systematically when one varies its content, and these content effects have been used to argue that the human cognitive architecture contains a number of domain-specific representation and inference systems, such as social contract algorithms and hazard management systems. Recently, however, Sperber, Cara & Girotto (Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57, 31-95) have proposed that relevance theory can explain performance on the selection task - including all content effects - without invoking inference systems that are content-specialized. Herein, we show that relevance theory alone cannot explain a variety of content effects - effects that were predicted in advance and are parsimoniously explained by theories that invoke domain-specific algorithms for representing and making inferences about (i) social contracts and (ii) reducing risk in hazardous situations. Moreover, although Sperber et al. (1995) were able to use relevance theory to produce some new content effects in other domains, they conducted no experiments involving social exchanges or precautions, and so were unable to determine which - content-specialized algorithms or relevance effects - dominate reasoning when the two conflict. When experiments, reported herein, are constructed so that the different theories predict divergent outcomes, the results support the predictions of social contract theory and hazard management theory, indicating that these inference systems override content-general relevance factors. The fact that social contract and hazard management algorithms provide better explanations for performance in their respective domains does not mean that the content-general logical procedures posited by relevance theory do not exist, or that relevance effects never occur. It does mean, however, that one needs a principled way of explaining which effects will dominate when a set of inputs activate more than one reasoning system. We propose the principle of pre-emptive specificity - that the human cognitive architecture should be designed so that more specialized inference systems pre-empt more general ones whenever the stimuli centrally fit the input conditions of the more specialized system. This principle follows from evolutionary and computational considerations that are common to both relevance theory and the ecological rationality approach.     

The probability heuristics model of syllogistic reasoning

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic.     

Validation of psychoanalytic theories: Towards a conceptualization of references

The authors discuss criteria for the validation of psychoanalytic theories and develop a heuristic and normative model of the references needed for this. Their core question in this paper is: can psychoanalytic theories be validated exclusively from within psychoanalytic theory (internal validation), or are references to sources of knowledge other than psychoanalysis also necessary (external validation)? They discuss aspects of the classic truth criteria correspondence and coherence, both from the point of view of contemporary psychoanalysis and of contemporary philosophy of science. The authors present arguments for both external and internal validation. Internal validation has to deal with the problems of subjectivity of observations and circularity of reasoning, external validation with the problem of relevance. They recommend a critical attitude towards psychoanalytic theories, which, by carefully scrutinizing weak points and invalidating observations in the theories, reduces the risk of wishful thinking. The authors conclude by sketching a heuristic model of validation. This model combines correspondence and coherence with internal and external validation into a four‐leaf model for references for the process of validating psychoanalytic theories.     

Relations between premise similarity and inductive strength

According to the diversity principle, diverse evidence is strong evidence. There has been considerable evidence that people respect this principle in inductive reasoning. However, exceptions may be particularly informative. Medin, Coley, Storms, and Hayes (2003) introduced a relevance theory of inductive reasoning and used this theory to predict exceptions, including the nondiversity-by-propertyreinforcement effect. A new experiment in which this phenomenon was investigated is reported here. Subjects made inductive strength judgments and similarity judgments for stimuli from Medin et al. (2003). The inductive strength judgments showed the same pattern as that in Medin et al. (2003); however, the similarity judgments suggested that the pattern should be interpreted as a diversity effect, rather than as a nondiversity effect. It is concluded that the evidence regarding the predicted nondiversity-byproperty-reinforcement effect does not give distinctive support for relevance theory, although this theory does address other results.     

Smarter than we think: when our brains detect that we are biased

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 (the "lawyer-engineer" problem) while the activation of brain regions believed to be involved in conflict detection (anterior cingulate) and response inhibition (lateral prefrontal cortex) 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.     

Toward understanding why fairness matters: the influence of mortality salience on reactions to procedural fairness

This article focuses on the question of why fairness matters to people. On the basis of fairness heuristic theory, the authors argue that people especially need fairness when they are uncertain about things that are important to them. Following terror management theory, the authors focus on a basic kind of human uncertainty: fear of death. Integrating these two theoretical frameworks, it is proposed that thinking about their mortality should make fairness a more important issue to people. The findings of three experiments support the authors' line of reasoning: Asking participants to think about their mortality led to stronger fair process effects (positive effects of perceived procedural fairness on subsequent reactions) than not asking them to think about mortality. It is argued that these findings suggest that fairness especially matters to people when they are uncertain about fundamental aspects of human life such as human mortality.     

Using dual-process theory and analogical transfer to explain facilitation on a hypothetico-deductive reasoning task

Using the analogical transfer paradigm, the present study investigated the competing explanations of Girotto and Legrenzi (Psychological Research 51: 129–135, 1993) and Griggs, Platt, Newstead, and Jackson (Thinking and Reasoning 4: 1–14, 1998) for facilitation on the SARS version of the THOG problem, a hypothetico-deductive reasoning task. Girotto and Legrenzi argue that facilitation is based on logical analysis of the task [System 2 reasoning in Evans’s (Trends in Cognitive Sciences 7: 454–459, 2003) dual-process account of reasoning] while Griggs et al. maintain that facilitation is due to an attentional heuristic produced by the wording of the problem (System 1 reasoning). If Girotto and Legrenzi are correct, then System 2 reasoning, which is volitional and responsible for deductive reasoning, should be elicited, and participants should comprehend the solution principle of the THOG task and exhibit analogical transfer. However, if Griggs et al. are correct, then System 1 reasoning, which is responsible for heuristic problem solving strategies such as an attentional heuristic, should occur, and participants should not abstract the solution principle and transfer should not occur. Significant facilitation (68 and 82% correct) was only observed for the two SARS source problems, but significant analogical transfer did not occur. This lack of transfer suggests that System 1 reasoning was responsible for the facilitation observed in the SARS problem, supporting Griggs et al.’s attentional heuristic explanation. The present results also underscore the explanatory value of using analogical transfer rather than facilitation as the criterion for problem understanding.     

推理偏差:冲突察觉还是冲突抑制的失败?

双系统理论认为人类在推理过程中存在着两种类型的加工方式:一种为快速的、不受工作记忆资源影响的启发式加工; 一种为慢速的、受认知资源限制的分析式加工。通过对这两种加工类型互相作用方式的深入研究,目前已经形成了不同的加工模型,意图解决核心问题——推理偏差产生的原因。本研究从双系统加工模型入手,结合最新的行为、训练以及神经机制的研究,对导致推理偏差的原因究竟是冲突察觉还是冲突抑制的失败进行详细分析     

A transitive-chain theory of syllogistic reasoning

A new theory of syllogistic reasoning, called the transitive-chain theory, is presented. The transitive-chain theory proposes that information about set relations is represented in memory by pairs of informational components. The theory further proposes that information about set relations is integrated by applying a small set of rules to transitive chains of these set relations. The rules that are applied to these chains are specified in detail. The theory is cast in terms of information-processing models for variants of the syllogistic reasoning task, and then mathematical models that quantify each of these information-processing models are presented. In a series of five experiments, the transitive-chain theory provides a good account of the response-choice data for syllogisms with various types of content, quantifiers, and logical relations (categorical and conditional). The results of these experiments offer tentative answers to four issues in the theory of syllogistic reasoning: (a) representation of premise information; (b) combination of premise information; (c) sources of difficulty in syllogistic reasoning; and (d) generality of the processes used in syllogistic reasoning.     

Uncertainty management: the influence of uncertainty salience on reactions to perceived procedural fairness.

On the basis of fairness heuristic theory, it is argued in this article that people especially need fairness when they are reminded about aspects of their lives that make them uncertain. It is therefore proposed that thinking about uncertainty should make fairness a more important issue to people. The findings of 3 experiments support this line of reasoning: Asking (vs. not asking) participants 2 questions that solicited their thoughts and feelings of being uncertain led to stronger effects of perceived procedural fairness on participants' affective reactions toward the way they were treated. It is argued that these findings suggest that fairness matters to people especially when they are trying to deal with things that make them uncertain. An implication of the current findings therefore may be that fairness is important to people because it gives them an opportunity to manage uncertain aspects of their lives.     

Mental models and probabilistic thinking

This paper outlines the theory of reasoning based on mental models, and then shows how this theory might be extended to deal with probabilistic thinking. The same explanatory framework accommodates deduction and induction: there are both deductive and inductive inferences that yield probabilistic conclusions. The framework yields a theoretical conception of strength of inference, that is, a theory of what the strength of an inference is objectively: it equals the proportion of possible states of affairs consistent with the premises in which the conclusion is true, that is, the probability that the conclusion is true given that the premises are true. Since there are infinitely many possible states of affairs consistent with any set of premises, the paper then characterizes how individuals estimate the strength of an argument. They construct mental models, which each correspond to an infinite set of possibilities (or, in some cases, a finite set of infinite sets of possibilities). The construction of models is guided by knowledge and beliefs, including lay conceptions of such matters as the “law of large numbers”. The paper illustrates how this theory can account for phenomena of probabilistic reasoning.     

When can we say 'if'?

In this study, we focus on the conditions which permit people to assert a conditional statement of the form 'if p then q' with conversational relevance. In a broadly decision-theoretic approach, also drawing on hypothetical thinking theory [Evans, J. St. B. T. (2007). Hypothetical thinking: Dual processes in reasoning and judgement. Hove, UK: Psychology Press.], we predicted that conditional tips and promises would appear more useful and persuasive and be more likely to encourage an action p when (a) the conditional link from p to q was stronger, (b) the cost of the action p was lower and (c) the benefit of the consequence q was higher. Similarly, we predicted that conditional warnings and threats would be seen as more useful and persuasive and more likely to discourage an action p when (a) the conditional link from p to q was stronger, (b) the benefit of the action p was lower and (c) the cost of the consequence q was higher. All predictions were strongly confirmed, suggesting that such conditionals may best be asserted when they are of high relevance to the goals of the listener.     

Counterfactual reasoning and the problem of selecting antecedent scenarios

A recent group of social scientists have argued that counterfactual questions play an essential role in their disciplines, and that it is possible to have rigorous methods to investigate them. Unfortunately, there has been little (if any) interaction between these social scientists and the philosophers who have long held that rigorous counterfactual reasoning is possible. In this paper, I hope to encourage some fresh thinking on both sides by creating new connections between them. I describe what I term “problem of selecting antecedent scenarios,” and show that this is an essential challenge in real-life counterfactual reasoning. Then, I demonstrate that the major extant theories of counterfactuals (especially the Lewis/Stalnaker theory and Igal Kvart’s rival account) are unable to solve this problem. I show that there are instances of real-life counterfactual reasoning in the social sciences that are counterexamples to both of these accounts. And finally, I develop a new theory of how to select antecedent scenarios that overcomes these difficulties, and so would be part of a more adequate theory of counterfactuals (and counterfactual reasoning).