The biases that arise due to how people perceive, think, remember, and represent events and phenomena and use these heuristics in their problem-solving and decision-making.
Related Terms: Computational/Model Bias, Data Bias
Heuristics or preferences that we have in solving problems or making decisions can be a source of bias. Biases in problem solving can be described as stemming more fundamentally from how people perceive, think, remember, and represent events and phenomena – both strategically and inadvertently, keeping in mind that all of these are extremely context dependent, much more than it seems most people realize.
For example, people are likely to perceive motion and color, which are more salient to them than orientation, and may be limited in their understanding of complexity by working memory limits (5 plus or minus two), and their ability to perceive categories – which can be greatly facilitated by expertise and an understanding of hierarchical relationships within data.
Of relevance to the definition of biases, Kahneman has suggested that most common heuristics can be characterized as resulting from “attribute substitution” – for example, people commonly substitute feelings/emotions in part or entirely for cognitive assessments, or mental availability/accessibility (i.e., does it come readily to mind) for more cognitive or deliberative assessments of prevalence / relative frequency. Another common type of bias is anchoring, where subjective estimates can be disproportionately influenced by some familiar or salient number for example, and adjust their estimates insufficiently away from that anchor. An example of a heuristic that can be hugely influential is a preference to use models and tools with which you are familiar.
“Narrow bracketing” has been highlighted in the judgment and decision making literature as a weakness in intuitive problem solving approaches (related to smaller variance). Even more specifically, people often use lexicographic approaches to problem solving, considering only one aspect or one option at a time, which might similarly result in ‘narrow bracketing’ of problems.
Resources and References
- Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. Heuristics and biases: The psychology of intuitive judgment, 49, 81.
- Read, D., Loewenstein, G., Rabin, M., Keren, G., & Laibson, D. (1999). Choice bracketing. In Elicitation of preferences (pp. 171-202). Springer, Dordrecht.