Early studies of intuitive judgment and decision making conducted with the late Amos Tversky are reviewed in the context of two related concepts: an analysis of accessibility, the ease with which thoughts come to mind; a distinction between effortless intuition and deliberate reasoning. Intuitive thoughts, like percepts, are highly accessible. Determinants and consequences of accessibility help explain the central results of prospect theory, framing effects, the heuristic process of attribute substitution, and the characteristic biases that result from the substitution of nonextensional for extensional attributes. Variations in the accessibility of rules explain the occasional corrections of intuitive judgments. The study of biases is compatible with a view of intuitive thinking and decision making as generally skilled and successful.

this paper is to show that this misunderstanding of the nature of logic by these and other prominent programs of research into human reasoning, has led to an impoverishment of empirical investigation into what subjects are doing in the selection task and to a wholly unnecessary and damaging rift between logically based cognitive theories of natural language interpretation on the one hand, and psychological experimentation on reasoning on the other. We will show that when empirical exploration is based on an informed understanding of logically based cognitive theory, the evidence strongly suggests a nearly opposite evolutionary account of the relation between the emergence of human communication capacities and economic exchange, and that logical semantics already has accounts of context senstivity to o#er far in advance of mental models theory's new creations

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Much research on judgment and decision making has focussed on the adequacy of classical rationality as a description of human reasoning. But more recently it has been argued that classical rationality should also be rejected even as normative standards for human reasoning. For example, Gigerenzer and Goldstein (1996) and Gigerenzer and Todd (1999a) argue that reasoning involves ‘‘fast and frugal’ ’ algorithms which are not justified by rational norms, but which succeed in the environment. They provide three lines of argument for this view, based on: (A) the importance of the environment; (B) the existence of cognitive limitations; and (C) the fact that an algorithm with no apparent rational basis, Take-the-Best, succeeds in an judgment task (judging which of two cities is the larger, based on lists of features of each city). We reconsider (A)–(C), arguing that standard patterns of explanation in psychology and the social and biological sciences, use rational norms to explain why simple cognitive algorithms can succeed. We also present new computer simulations that compare Take-the-Best with other cognitive models (which use connectionist, exemplarbased, and decision-tree algorithms). Although Take-the-Best still performs well, it does not perform noticeably better than the other models. We conclude that these results provide no strong reason to prefer Take-the-Best over alternative cognitive models.

Humans appear to reason using two processing styles: System 1 processes that are quick, intuitive, and effortless and System 2 processes that are slow, analytical, and deliberate that occasionally correct the output of System 1. Four experiments suggest that System 2 processes are activated by metacognitive experiences of difficulty or disfluency during the process of reasoning. Incidental experiences of difficulty or disfluency—receiving information in a degraded font (Experiments 1 and 4), in difficultto-read lettering (Experiment 2), or while furrowing one’s brow (Experiment 3)—reduced the impact of heuristics and defaults in judgment (Experiments 1 and 3), reduced reliance on peripheral cues in persuasion (Experiment 2), and improved syllogistic reasoning (Experiment 4). Metacognitive experiences of difficulty or disfluency appear to serve as an alarm that activates analytic forms of reasoning that assess and sometimes correct the output of more intuitive forms of reasoning.

People often choose intuitive rather than equally valid nonintuitive alternatives. The authors suggest that these intuitive biases arise because intuitions often spring to mind with subjective ease, and the subjective ease leads people to hold their intuitions with high confidence. An investigation of predictions against point spreads found that people predicted intuitive options (favorites) more often than equally valid (or even more valid) nonintuitive alternatives (underdogs). Critically, though, this effect was largely determined by people’s confidence in their intuitions (intuitive confidence). Across naturalistic, expert, and laboratory samples (Studies 1–3), against personally determined point spreads (Studies 4–11), and even when intuitive confidence was manipulated by altering irrelevant aspects of the decision context (e.g., font; Studies 12 and 13), the authors found that decreasing intuitive confidence reduced or eliminated intuitive biases. These findings indicate that intuitive biases are not inevitable but rather predictably determined by contextual variables that affect intuitive confidence.

When participants assess the relationship between two variables, each with levels of presence and absence, the two most robust phenomena are that: (a) observing the joint presence of the variables has the largest impact on judgment and observing joint absence has the smallest impact, and (b) participants’ prior beliefs about the variables ’ relationship influence judgment. Both phenomena represent departures from the traditional normative model (the phi coefficient or related measures) and have therefore been interpreted as systematic errors. However, both phenomena are consistent with a Bayesian approach to the task. From a Bayesian perspective: (a) joint presence is normatively more informative than joint absence if the presence of variables is rarer than their absence, and (b) failing to incorporate prior beliefs is a normative error. Empirical evidence is reported showing that joint absence is seen as more informative than joint presence when it is clear that absence of the variables, rather than their presence, is rare.

An important research tradition in the cognitive psychology of reasoning--called the heuristics and biases approach--has firmly established that people’s responses often deviate from the performance considered normative on many reasoning tasks. For example, people assess probabilities incorrectly, they display confirmation bias, they test hypotheses inefficiently, they violate the axioms of utility theory, they do not properly calibrate degrees of belief, they overproject their own opinions onto others, they display illogical framing effects, they uneconomically honor sunk costs, they allow prior knowledge to become implicated in deductive reasoning, and they display numerous other information processing biases (for summaries of the large literature, see

General intelligence (g) poses a problem for evolutionary psychology’s modular view of the human brain. The author advances a new evolutionary psychological theory of the evolution of general intelligence and argues that general intelligence evolved as a domain-specific adaptation for the originally limited sphere of evolutionary novelty in the ancestral environment. It has accidentally become universally important merely because we now live in an evolutionarily novel world. The available data seem to support the author’s contention that intelligent people can solve problems better than less intelligent people only if the problems are evolutionarily novel, and they have no advantage in solving evolutionarily familiar problems. This perspective can also solve some empirical anomalies, such as the “central theoretical problem of human sociobiology ” (D. R. Vining, 1986, p. 167) and the geographic distribution of general intelligence throughout the world. The g factor is actually a biologically based variable, which, like other biological functions in the human species, is necessarily a product of the evolutionary process. (Jensen, 1998, p. xii) The existence of the g factor (the “general intelligence ” factor) in psychometrics appears to contradict the strong modularity view of the mind. (Miller, 2000, p. 42)

Acknowledgements: This paper was prepared with support from the Division of Behavioral and