Why do we take mental shortcuts?

Heuristics

, explained.
Bias

What are Heuristics?

Heuristics are mental shortcuts that can facilitate problem-solving and probability judgments. These strategies are generalizations, or rules-of-thumb, that reduce cognitive load. They can be effective for making immediate judgments, however, they often result in irrational or inaccurate conclusions.

A stick figure on the left holding a red apple with a speech bubble saying 'Would you like this apple?' Another stick figure on the right, looking uncertain, has a larger speech bubble filled with various thoughts, such as 'Glucose levels: 43%' and 'Risk of poison: >0%' with arrows pointing to the apple and leading to the word 'YUMMY!' at the bottom. The background features an abstract color gradient with the word 'HEURISTICS' at the top.

Where this bias occurs

We use heuristics in all sorts of situations. For example, one type of heuristic, the availability heuristic, often happens when we’re attempting to judge the frequency with which a certain event occurs. Say someone asked you whether more tornadoes occur in Kansas or Nebraska. Most of us can quickly call to mind an example of a tornado in Kansas: the tornado that whisked Dorothy Gale off to Oz in Frank L. Baum’s The Wizard of Oz. Although it’s fictional, this example comes to us easily. On the other hand, most people have a lot of trouble calling to mind an example of a tornado in Nebraska. This leads us to believe tornadoes are more common in Kansas than in Nebraska. However, the two states report similar tornado activity.1

Heuristics don’t just pop up when we’re trying to predict probability. Simple heuristics show up across various domains of life, streamlining the brain’s decision-making process in the same way that keyboard shortcuts help us copy and paste text or switch between browser tabs. Like keyboard shortcuts we all know and love, heuristics are a problem-solving approach involving mental shortcuts that help us make decisions easier and faster.

Unfortunately, our cognitive time-savers are not always as accurate or reliable as the ones programmed into our computers. Just as the availability heuristic can cause us to judge the probability of a tornado in Nebraska inaccurately, heuristics often lead us to “good enough” conclusions that seem correct based on our previous experiences or pre-existing ideas but may not be objectively accurate. Why? Our brains often revert to heuristics when finding an optimal solution isn’t possible or practical—for example, you cannot evaluate every single restaurant in a big city before choosing a place to eat, so heuristics step in to help you make a decision that is likely to be satisfactory, even if it’s not optimal.

Sources

  1. Gilovich, T., Keltner, D., Chen. S, and Nisbett, R. (2015). Social Psychology (4th edition). W.W. Norton and Co. Inc.
  2. Tversky, A. and Kahneman, D. (1974). Judgment Under Uncertainty: Heuristics and Biases. Science. 185(4157), 1124-1131.
  3. See 2
  4. See 2
  5. See 2
  6. Mervis, C. B., & Rosch, E. (1981). Categorization of natural objects. Annual Review of Psychology, 32(1), 89–115. https://doi.org/10.1146/annurev.ps.32.020181.000513
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  9. Epley, N., & Gilovich, T. (2006). The anchoring-and-adjustment heuristic. Psychological Science -Cambridge-, 17(4), 311–318.
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  11. System 1 and System 2 Thinking. The Marketing Society. https://www.marketingsociety.com/think-piece/system-1-and-system-2-thinking
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  14. Aggarwal, P., Jun, S. Y., & Huh, J. H. (2011). Scarcity messages. Journal of Advertising, 40(3), 19–30.
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  17. Devine, P. G. (1989). Stereotypes and prejudice: their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18. https://doi.org/10.1037/0022-3514.56.1.5
  18. Kuo, L., Chang, T., & Lai, C.-C. (2022). Research on product design modeling image and color psychological test. Displays, 71, 102108. https://doi.org/10.1016/j.displa.2021.102108
  19. Murata, A., Nakamura, T., & Karwowski, W. (2015). Influence of cognitive biases in distorting decision making and leading to critical unfavorable incidents. Safety, 1(1), 44-58. https://doi.org/10.3390/safety1010044

About the Authors

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Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

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Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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