Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon’s notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the authors held a competition between the satisficing “Take The Best ” algorithm and various “rational ” inference procedures (e.g., multiple regression). The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. Organisms make inductive inferences. Darwin (1872/1965) observed that people use facial cues, such as eyes that waver and lids that hang low, to infer a person’s guilt. Male toads, roaming through swamps at night, use the pitch of a rival’s croak to infer its size when deciding whether to fight (Krebs & Davies, 1987). Stock brokers must make fast decisions about which of several stocks to trade or invest when only limited information is available. The list goes on. Inductive

Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a variety of guises and gives examples of its operation in several practical contexts. Possible explanations are considered, and the question of its utility or disutility is discussed. When men wish to construct or support a theory, how they torture facts into their service! (Mackay, 1852/ 1932, p. 552) Confirmation bias is perhaps the best known and most widely accepted notion of inferential error to come out of the literature on human reasoning. (Evans, 1989, p. 41) If one were to attempt to identify a single problematic aspect of human reasoning that deserves attention above all others, the confirmation bias would have to be among the candidates for consideration. Many have written about this bias, and it appears to be sufficiently strong and pervasive that one is led to wonder whether the bias, by itself, might account for a significant fraction of the disputes, altercations, and misunderstandings that occur among individuals, groups, and nations. Confirmation bias has been used in the psychological literature to refer to a variety of phenomena. Here I take the term to represent a generic concept that subsumes several more specific ideas that connote the inappropriate bolstering of hypotheses or beliefs whose truth is in question.

People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do; they are subject to an illusion—an illusion of explanatory depth. The illusion is far stronger for explanatory knowledge than many other kinds of knowledge, such as that for facts, procedures or narratives. The illusion for explanatory knowledge is most robust where the environment supports real-time explanations with visible mechanisms. We demonstrate the illusion of depth with explanatory knowledge in Studies 1–6. Then we show differences in overconfidence about knowledge across different knowledge domains in Studies 7–10. Finally, we explore the mechanisms behind the initial confidence and behind overconfidence in Studies 11 and 12, and discuss the implications of our findings for the roles of intuitive theories in concepts and cognition.

Please do not quote or cite without permission of the authors Overconfidence in interval estimates 2 Many studies over the last several decades have found that people are generally overconfident about the accuracy of their knowledge. This generalization has been overturned by a number of recent, carefully controlled studies. These studies show little or no overall bias when judges express confidence in a choice between two alternative answers to a question. Apparent overconfidence is due primarily to unsystematic error in judgments, combined with an unrepresentative selection of task items. However, Klayman et al. (1999), found that substantial overconfidence persisted under equivalently controlled conditions with a different type of confidence judgment. When judges are asked to provide intervals such that they are x % sure the correct answer is within the interval, the answer falls inside their interval much less than x % of the time. The present paper shows that, although unsystematic judgmental error may contribute to overconfidence, subjective confidence intervals are indeed systematically too narrow—

We experimentally test overconfidence in investment decisions by offering participants the possibility to substitute their own for alternative investment choices.

Experiments in psychology, where subjects estimate confidence intervals to a series of factual questions, have shown that individuals report far too narrow intervals. This has been interpreted as evidence of overconfidence in the preciseness of knowledge, a potentially serious violation of the rationality assumption in economics. Following these results a growing literature in economics has incorporated overconfidence in models of, for instance, financial markets. In this paper we investigate the robustness of results from confidence interval estimation tasks with respect to a number of manipulations: frequency assessments, peer frequency assessments, iteration, and monetary incentives. Our results suggest that a large share of the overconfidence in interval estimation tasks is an artifact of the response format. Using frequencies and monetary incentives reduces the measured overconfidence in the confidence interval method by about 65%. The results are consistent with the notion that subjects have a deep aversion to setting broad confidence intervals, a reluctance that we attribute to a socially rational trade-off between informativeness and accuracy.

Confidence in decision making is an important dimension of managerial behavior. However, what is the relation between confidence, on the one hand, and the fact of receiving or expecting to receive feedback on decisions taken, on the other hand? To explore this and related issues in the context of everyday decision making, use was made of the ESM (Experience Sampling Method) to sample decisions taken by undergraduates and business executives. For several days, participants received 4 or 5 SMS messages daily (on their mobile telephones) at random moments at which point they completed brief questionnaires about their current decision making activities. Issues considered here include differences between the types of decisions faced by the two groups, their structure, feedback (received and expected), and confidence in decisions taken as well as in the validity of feedback. No relation was found between confidence in decisions and whether participants received or expected to receive feedback on those decisions. In addition, although participants are clearly aware that feedback can provide both “confirming ” and “disconfirming ” evidence, their ability to specify appropriate feedback is imperfect. Finally, difficulties experienced in using the ESM are discussed as are possibilities for further research using this methodology.

How do we make decisions? According to subjective expected utility (SEU) theory, which still holds sway throughout much of the social sciences, “decision makers behave as if utilities were assigned to outcomes, probabilities were attached states of nature, and decisions were made by taking expected utilities ” (Mas-Collel, Whinston, & Green, 1995, p. 206). Although this is an elegant and often useful way to model decision outcomes, it imposes heroic knowledge and rationality requirements, and it clearly does not reflect the way people make decisions most of the time. 1 Herbert Simon (1956) was the most outspoken critic of the assumption that SEU theory can be applied in any literal way to human choices. In his view, “the SEU model is a beautiful object deserving a prominent place in Plato’s heaven of ideas ” (1990a, p. 194); real humans, however, “have neither the facts nor the consistent structure of values nor the reasoning power at their disposal that would be required... to apply SEU principles ” (p. 197). Simon did not limit himself to criticizing the “Olympian model ” of SEU theory (Simon, 1990a, p. 198); he also proposed an alternative way to think about decision making, which he called bounded rationality. Simon's