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Abstract When they are asked to test a given hypothesis, individuals tend to be biased towards confirming evidence. This phenomenon has been documented on different cognitive components: information search, weighing of evidence, and memory recall. However, the interpretation of these observations has been debated, and it remains unclear whether they truly reflect a confirmation bias (as opposed to e.g., a bias towards positive information). In the present study we aimed at evaluating whether these biases might be subtended by a common factor. We adapted three classic experimental paradigms on hypothesis testing (Wason selection task, 2-4-6 task, and interviewee task) and examined the relation between these biases using an individual differences approach. Participants (N = 200) completed a total of nine behavioral tasks, in which each component of confirmation bias was measured in each of the three experimental paradigms. Correlations and factor analyses within a multitrait–multimethod framework indicated greater convergence of bias scores within each component across paradigms, than within experimental paradigms. This suggests that a common factor underlies the different measurements of confirmation bias across experimental paradigms, at least to some extent. In these paradigms, thus, biases towards confirming evidence may truly reflect a confirmation bias.

Over the last two decades, there has been a growing interest in the study of individual differences in how people’s judgments and decisions deviate from normative standards. We conducted a systematic review of heuristics-and-biases tasks for which individual differences and their reliability were measured, which resulted in 41 biases measured over 108 studies, and suggested that reliable measures are still needed for some biases described in the literature. To encourage and facilitate future studies on heuristics and biases, we centralized the task materials in an online resource: The Heuristics-and-Biases Inventory (HBI; https://sites.google.com/view/hbiproject). We discuss how this inventory might help research progress on major issues such as the structure of rationality (single vs. multiple factors) and how biases relate to cognitive ability, personality, and real-world outcomes. We also consider how future research should improve and expand the HBI.

The author reviewed the research on the impact of cognitive biases on professionals’ decision-making in four occupational areas (management, finance, medicine, and law). Two main findings emerged. First, the literature reviewed shows that a dozen of cognitive biases has an impact on professionals’ decisions in these four areas, overconfidence being the most recurrent bias. Second, the level of evidence supporting the claim that cognitive biases impact professional decision-making differs across the areas covered. Research in finance relied primarily upon secondary data while research in medicine and law relied mainly upon primary data from vignette studies (both levels of evidence are found in management). Two research gaps are highlighted. The first one is a potential lack of ecological validity of the findings from vignette studies, which are numerous. The second is the neglect of individual differences in cognitive biases, which might lead to the false idea that all professionals are susceptible to biases, to the same extent. To address that issue, we suggest that reliable, specific measures of cognitive biases need to be improved or developed.

Individual differences have been neglected in decision-making research on heuristics and cognitive biases. Addressing that issue requires having reliable measures. The author first reviewed the research on the measurement of individual differences in cognitive biases. While reliable measures of a dozen biases are currently available, our review revealed that some measures require improvement and measures of other key biases are still lacking (e.g., confirmation bias). We then conducted empirical work showing that adjustments produced a significant improvement of some measures and that confirmation bias can be reliably measured. Overall, our review and findings highlight that the measurement of individual differences in cognitive biases is still in its infancy. In particular, we suggest that contextualized (in addition to generic) measures need to be improved or developed.

Redistribution preferences depend on factors such as self-interest and political views. Recently, Deffains et al. (2016) reported that redistributive behavior is also sensitive to the actual experience of success or failure in a real effort task. While successful participants ('overachievers') are more likely to attribute their success to their effort rather than luck and opt for less redistribution, unsuccessful participants ('underachievers') tend to attribute their failure to external factors and opt for more redistribution. The aim of the present study was to test how the experience of success (symbolic success) and political views interact in producing redistributive behavior in an experimental setting. The study was conducted during the 2017 French presidential election. Our sample was biased towards left-wing, and most participants reported voting for Mélenchon, Hamon or Macron. Our findings reveal that 1) Macron voters redistribute less than Hamon voters who themselves redistribute less than Mélenchon voters, 2) overachievers redistribute less than underachievers only among Mélenchon voters. This suggests that redistributive behavior is governed primarily by political opinions, and that influence by exogenous manipulation of symbolic success is not homogenous across left-wing political groups.