BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificial intelligence technology that models uncertain situations, supporting better probabilistic and causal reasoning and decision making.

An investigation of the role of some person and situation variables in multiple cue probability learning.

Making decisions using judgements of multiple non-deterministic indicators is an important task, both in everyday and professional life. Learning of such decision making has often been studied as the mapping of stimuli (cues) to an environmental variable (criterion); however, little attention has been paid to the effects of situation-by-person interactions on this learning. Accordingly, we manipulated cue and feedback presentation mode (graphic or numeric) and task difficulty, and measured individual differences in working memory capacity (WMC).

The aggregation of expert judgment: do good things come to those who weight?

Good policy making should be based on available scientific knowledge. Sometimes this knowledge is well established through research, but often scientists must simply express their judgment, and this is particularly so in risk scenarios that are characterized by high levels of uncertainty. Usually in such cases, the opinions of several experts will be sought in order to pool knowledge and reduce error, raising the question of whether individual expert judgments should be given different weights.

Market entry decisions: effects of absolute and relative confidence.

In a market entry game, the number of entrants usually approaches game-theoretic equilibrium quickly, but in real-world markets business start-ups typically exceed market capacity, resulting in chronically high failure rates and suboptimal industry profits. Excessive entry has been attributed to overconfidence arising when expected payoffs depend partly on skill. In an experimental test of this hypothesis, 96 participants played 24 rounds of a market entry game, with expected payoffs dependent partly on skill on half the rounds, after their confidence was manipulated and measured.

An empirical test of the relative validity of expert and lay judgments of risk.

This article investigates how accurately experts (underwriters) and lay persons (university students) judge the risks posed by life-threatening events Only one prior study (Slovic, Fischhoff, & Lichtenstein, 1985) has previously investigated the veracity of expert versus lay judgments of the magnitude of risk. In that study, a heterogeneous grouping of 15 experts was found to judge, using marginal estimations, a variety of risks as closer to the true annual frequencies of death than convenience samples of the lay population. In this study, we use a larger, homogenous sample of experts performing an ecologically valid task.