The overconfidence observed in calibration studies has recently been questioned on both psychological and methodological grounds. In the first part of the article we discuss these issues and argue that overconfidence cannot be explained as a selection bias, and that it is not eliminated by random sampling of questions. In the second part of the article, we compare probability judgments
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2003, Artificial Intelligence
Many works in the past showed that human judgments of uncertainty do not conform very well to probability theory. The present paper reports four experiments that were conducted in order to evaluate if human judgments of uncertainty conform better to possibility theory. At first, two experiments investigate the descriptive properties of some basic possibilistic measures. Then a new measurement apparatus is used, the Ψ-scale, to compare possibilistic vs. probabilistic disjunction and conjunction. Results strongly suggest that a human judgment is qualitative in essence, closer to a possibilistic than to a probabilistic approach of uncertainly. The paper also describes a qualitative heuristic, for conjunction, which was used by expert radiologists.
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1995, The Knowledge Engineering Review
The claim is frequently made that human judgement and reasoning are vulnerable to cognitive biases. Such biases are assumed to be inherent in that they are attributed to the nature of the mental processes that produce judgement. In this paper, we review the psychological evidence for this claim in the context of the debate concerning human judgemental competence under uncertainty. We consider recent counter-arguments which suggest that the evidence for cognitive biases may be dependent on observations of performance on inappropriate tasks and by comparisons with inappropriate normative standards. We also consider the practical implications for the design of decision support systems.
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1996, Journal of Experimental Psychology: Applied
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1993, Psychological Bulletin
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Abstract. We propose a method for estimating subjective beliefs, viewed as a subjective probability distribution. The key insight is to characterize beliefs as a parameter to be estimated from observed choices in a well-defined experimental task, and to estimate that parameter as a random coefficient. The experimental task consists of a series of standard lottery choices in which the subject is assumed to use conventional risk attitudes to select one lottery or the other, and then a series of betting choices in which the subject is presented with a range of bookies offering odds on the outcome of some event that the subject has a belief over. Knowledge of the risk attitudes of subjects conditions the inferences about subjective beliefs. Maximum simulated likelihood methods are used to estimate a structural model in which subjects employ subjective beliefs to make bets. We present evidence that some subjective probabilities are indeed best characterized as probability distributions w.
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2011, Quality & Quantity
According to a consolidated tradition of research about the psychology of decisions (Newell et al. 2007) and the psychometric psychology (Sartori 2008), the present study aims at analysing the preferences of individuals between the main numeric expressions of uncertainty: the probabilistic form (expressed by percentages) and the fractional form (expressed by fractions). The purpose is to verify a different management of
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2008, Thinking & Reasoning
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1997, Journal of Behavioral Decision Making
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2000, Prediction: Science, Decision Making, and the …
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1997, Organizational Behavior and Human Decision Processes
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2000, SSRN Electronic Journal
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1994, Psychological Bulletin
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The difficulty in deciding and facing up to uncertainty is not only linked to the inadequacy of the architecture of our minds but also to an ‘external’ model of uncertainty which does not correspond to the way in which our mind naturally functions. New conceptual paradigms and new programmes for experimental research are called for in order to redefine the role of internal and external restric- tions on human action (resources and available information, limitations on calcula- tion ability, on the capacity of memory, cognitive styles, gender differences and so on). All this should be contemplated in a more general theoretical framework – natural logic – based not on metaphysical assumptions but on the concrete evi- dence provided by cognitive neurosciences.
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2016, International Journal of Statistics and Probability
In the domain of the logic of certainty we examine the objective notions of the subjective probability with the clear aim of identifying their fundamental characteristics before the assignment, by the individual, of the probabilistic evaluation. Probability is an additional and subjective notion that one applies within the range of possibility, thus giving rise to those gradations, more or less probable, that are meaningless in the logic of certainty. Each criterion for evaluations under conditions of uncertainty is a device or instrument for obtaining a measurement; it furnishes an operational definition of probability or prevision P and together with the corresponding conditions of coherence can be taken as a foundation for the entire theory of probability. When we examine these criteria and their corresponding conditions of coherence we show the inevitable dichotomy between the subjective or psychological or empirical aspect of probability and the objective or logical or geometri.
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and the Logical or Geometrical One" />
1996, International Journal of Approximate Reasoning
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1984, Acta Psychologica
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2012, Frontiers in Neuroscience
The study of uncertainty in decision-making is receiving greater attention in the fields of cognitive and computational neuroscience. Several lines of evidence are beginning to elucidate different variants of uncertainty. Particularly, risk, ambiguity, and expected and unexpected forms of uncertainty are well articulated in the literature. In this article we review both empirical and theoretical evidence arguing for the potential distinction between three forms of uncertainty; expected uncertainty, unexpected uncertainty, and volatility. Particular attention will be devoted to exploring the distinction between unexpected uncertainty and volatility which has been less appreciated in the literature. This includes evidence mainly from neuroimaging, neuromodulation, and electrophysiological studies. We further address the possible differentiation of cognitive control mechanisms used to deal with these forms of uncertainty. Finally, we explore whether the dual modes of control theory provides a theoretical framework for understanding the distinction between unexpected uncertainty and volatility.
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