The heuristics-and-biases research program introduced by Tversky and Kahneman in the early 1970s (Kahneman & Tversky, 1973; Tversky & Kahneman, 1972, 1974) is a descriptive approach of rationality which consists of invoking heuristics (mental shortcuts) to explain systematic errors (biases) that people make in decision-making tasks. Since its inception, this research has produced a large literature on errors in judgment and decision-making (Gilovich et al., 2002). 

While research on heuristics and biases has been primarily conducted at the group level, there is a growing interest for individual differences. However, finding reliable measures of individual differences in heuristics and biases can be difficult and time-consuming. The HBI aims to centralize all available measures to facilitate access and encourage their use. Each measure is a behavioral task allowing one to calculate individual scores. 

The HBI can be used for investigating several research topics.

Are biases universal? 

The repeated observation that irrelevant factors produce biases in decision-making tasks has led to the assumption that such biases are universal, similarly to optical illusions (Kahneman, 2003). This inference is fallacious, as noted by Baron (2008). The observation of a significant bias at the group level does not imply that the bias is present in each individual. 

There are now clear evidences of systematic, reliable individual differences in performance on HB tasks (e.g., Berthet, Autissier, & de Gardelle, 2022; Bruine de Bruin et al., 2007; Burgoyne et al., 2021; Erceg et al., 2022; Stanovich & West, 1998, 2008; Teovanović et al., 2015; Toplak et al., 2011, 2014). 

It is true that some biases can be observed in most people. For instance, Gächter et al. (2022) found that 82% of participants exhibit an endowment effect: they are willing to sell a good that they have just been given at a price higher than the price at which they would be willing to buy it. 

On the other hand, it has been repeatedly found that many people do not show biases. For instance, using a within-subject version of the Asian Disease Problem of Tversky and Kahneman (1981), where participants are asked to rate a decision problem that is framed either positively (gain) or negatively (loss), Li and Liu (2008) showed that 59% of the participants responded consistently in the loss and gain frames. Moreover, some people may show the reverse of the usual bias, as is the case with the disposition effect in finance for instance (Dhar & Zhu, 2006). 

The issue of whether and which biases are universal or not remains to be further addressed. Note that the HBI may help to assess whether biases are universal or not across individuals, but also across cultures. For instance, Mezulis et al. (2004) reported significant cultural differences between Asian, U.S., and Western samples in the self-serving attributional bias. 

References

• Baron, J. (2008). Thinking and deciding (4th ed.). New York: Cambridge University Press. 

• Berthet, V., Autissier, D., & de Gardelle, V. (2022). Individual differences in decision-making: A test of a one-factor model of rationality. Personality and Individual Differences, 189, 111485. 

• Bruine de Bruin, W., Parker, A. M., & Fischhoff, B. (2007). Individual differences in adult decision-making competence. Journal of Personality and Social Psychology, 92(5), 938-956. 

• Burgoyne, A. P., Mashburn, C. A., Tsukahara, J. S., Hambrick, D. Z., & Engle, R. W. (2021). Understanding the relationship between rationality and intelligence: a latent-variable approach. Thinking & Reasoning. 

• Erceg, N., Galić, Z., & Bubić, A. (2022). Normative responding on cognitive bias tasks: Some evidence for a weak rationality factor that is mostly explained by numeracy and actively open-minded thinking. Intelligence, 90, 101619. 

• Dhar, R., & Zhu, N. (2006). Up Close and Personal: Investor Sophistication and the Disposition Effect. Management Science, 52(5), 726–740. 

• Gächter, S., Johnson, E. J., & Herrmann, A. (2022). Individual-level loss aversion in riskless and risky choices. Theory and Decision, 92, 599-624. 

• Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697–720. 

• Li, S., & Liu, C.-J. (2008). Individual differences in a switch from risk-averse preferences for gains to risk-seeking preferences for losses: Can personality variables predict the risk preferences? Journal of Risk Research, 11(5), 673–686.

• Mezulis, A. H., Abramson, L. Y., Hyde, J. S., & Hankin, B. L. (2004). Is there a universal positivity bias in attributions? A meta-analytic review of individual, developmental, and cultural differences in the self-serving attributional bias. Psychological bulletin, 130(5), 711–747. 

• Stanovich, K. E., & West, R. F. (1998). Individual differences in rational thought. Journal of Experimental Psychology: General, 127(2), 161–188. 

• Stanovich, K. E., & West, R. F. (2008). On the relative independence of thinking biases and cognitive ability. Journal of personality and social psychology, 94(4), 672–695. 

• Teovanović, P., Knežević, G., & Stankov, L. (2015). Individual differences in cognitive biases: Evidence against one-factor theory of rationality. Intelligence, 50, 75–86. 

• Toplak, M. E., West, R. F., & Stanovich, K. E. (2011). The Cognitive Reflection Test as a predictor of performance on heuristics-and-biases tasks. Memory & cognition, 39(7), 1275–1289. 

• Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking & Reasoning, 20(2), 147–168. 

• Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.