The authors suggest that the "graininess" or precision of uncertain judgments involves a trade-off between 2 competing objectives: accuracy and informativeness. Decision-making under Uncertainty: Most significant decisions made in today’s complex environment are formulated under a state of uncertainty. Judgment under Uncertainty: Heuristics and Biases Ebook. Coarse (imprecise) judgments are less informative than finely grained judgments; however, they are likely to be more accurate. Many different definitions have been proposed. From a descriptive vantage point, submitted articles could focus on aspects of judgment and/or decision-making under uncertainty, in general, or on judgment and decision-making in a specific domain. This work concerns judgmental estimation of quantities under uncertainty. Our aim herein is to broaden the scope of a prior Research Topic on “Improving Bayesian Reasoning: What Works and Why?” to also include normative approaches that are not Bayesian.
Impossible d'ajouter l'article à votre liste. In making predictions and judgments under uncertainty, people do not appear to follow the calculus of chance or the statistical theory of prediction. In “Better together: reliable application of the post-9/11 and post-Iraq US intelligence tradecraft standards requires collective analysis,” Marcoci et al. Accordingly, we seek papers that address how and why people judge and decide as they do (descriptive focus), how they ideally ought to judge and decide (normative focus), and how their judgment and decision-making processes might be improved in practice (prescriptive focus). judgment under uncertainty: heuristics and biases citation. (eds.). Marc Alpert & Howard Raiffa - 1982 - In Daniel Kahneman, Paul Slovic & Amos Tversky (eds. 18 However, as they do, their confidence decreases and anger increases, thus shedding light on the experiential side of this well-documented phenomenon. This appears to be an important factor in explaining the low rates of accurate judgment.

The topic is Prospect Theory. ), Judgment Under Uncertainty: Heuristics and Biases. An increasing number of organizations are making use of panels of experts in order to provide assessments over key uncertainties. Keywords: 190--200. In “Imprecise uncertain reasoning: a distributional approach,” Kleiter develops an approach to using mental probability logic in concert with beta distributions, copulas, vines, and stochastic simulation to model imprecise and uncertain reasoning. *Correspondence: David R. Mandel, drmandel66@gmail.com, Front. In “Bayesian revision vs. information distortion,” Russo explains how a normative requirement of Bayesian reasoning—namely, that likelihoods should be independent of the prior probability—is routinely violated in all but the most contrived judgment problems where such violations are designed to be impossible. Last but not least, three papers draw on decision science to shed light on professional practices in forensics and national security intelligence. CrossRef Google Scholar Communicating uncertainty for each class of decision requires (i) characterizing uncertainty, by identifying the issues most relevant to the choice; (ii) assessing uncertainty, by summarizing that information in a useful form; and (iii) conveying uncertainty, by creating messages that afford decision makers the detail that their choices warrant. They find that participants were more averse to conflict and reacted more positively to communications that reflect imprecision. The business judgment rule helps to insulate a corporation's board of directors from frivolous allegations about the way it conducts business. The violations, Russo argues, occur because people strive for coherence and therefore seek to bring new evidence in line with their prior beliefs. Judgment under Uncertainty. In “Does fear increase search effort in more numerate people? They find that worry affects recommendations only in the higher severity context (cancer), whereas consideration of disease likelihood given a positive test result played a greater role in the lower severity context (hypertension). We welcome the submission of articles that test a broad range of strategies or heuristics for improving judgment and/or decision-making under uncertainty, including those currently used in specialized fields, which may not have undergone adequate scientific testing. Shelley E. Taylor - 1982 - In Daniel Kahneman, Paul Slovic & Amos Tversky (eds. Judgment, decision-making, uncertainty, probability, higher-order cognition. 4157. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Cognition, 108, 740–753. We further sought contributions that examined judgment and decision making under conditions of uncertainty, which we intentionally left loosely defined. Home; Uncategorized Judgment Under Emotional Certainty and Uncertainty: ... by hypnosis and were unaware of this effect of the hypnosis subsequently judged themselves to be less certain of the meaning of a poem than did both participants who were not hypnotized and participants who knew that ... Judgment under uncertainty: Heuristics and biases. In this Research Topic we take a broad view on uncertainty, permitting it to include events that are (a) uncertain but well defined both in terms of their extension and probability (i.e., Knightian risk), (b) uncertain and vaguely and/or ambiguously defined in such terms, and/or (c) subjects of partial or complete ignorance (i.e., epistemic uncertainty). Contributions that examined judgment and decision making under conditions of uncertainty state of uncertainty conflict and more... 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