Availability bias

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Availability bias can be defined as a misjudgment of risk. An assessment based on false assumptions. When a person thinks something is more likely than it actually is because they have heard, read, or talked about it a disproportionate number of times. In addition, it may be a situation that happened to someone earlier - and that person therefore projects it into the present or future.

The term availability bias goes back to psychologists Amos Tversky and Daniel Kahneman, who coined it in 1973. In their work at the time, they showed that people tend to overestimate the likelihood of a scenario occurring if they could easily imagine or remember it[1].

Applications

  • Education: A study by Fox looks at whether memory impairment affects judgment. In his study, two groups filled out a course evaluation form. One of the two test groups had to note two positive aspects about the course and two additional suggestions for improvement. In contrast, the second group had to write down 10 suggestions for improvement and two positive comments about the course. Both groups were then asked to rate the course on a scale from 1 to 7. The students who had more suggestions for improvement rated the course better as they found the information more difficult to remember. Most of the students in the group given 10 suggestions did not write more than 2 because they could not recall any other instances of dissatisfaction with the class. The students who were asked to give the easier rating with only two complaints rated the course more rigorously because they had less trouble remembering the information[2].
  • Perceived risk: A hypothetical event makes an event appear more likely by establishing causal relationships. However, these effects could also be caused by the availability heuristic, since subjective likelihood is increased by making an event easier to imagine. Availability heuristics often lead to risk-averse human behavior. This means trying to avoid dangerous situations even when the danger seems unlikely[3].


Author: Max Bachmann

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Footnotes

  1. Cheng, Li, Liu, 2020, pp. 3141-3143
  2. Fox, 2006, pp. 86-89
  3. Hertwig, Pachur, Steinmann, 2012, pp. 314-316

References