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2 results

  • Chapter 4 - Streetlight Effects

  • from Section 1 - Incentives, Context, and Capital
  • Mark P. Khurana, University of Copenhagen
  • Book:
    The Trajectory of Discovery
    Published online:
    06 April 2023
    Print publication:
    13 April 2023, pp 23-26

  • Summary

    One of the many pitfalls in science is that researchers are prone to psychological biases, one of which is the streetlight effect. The streetlight effect is a type of observational bias that occurs because people are more likely to search for something where it is easier to look. We are prone to studying things that are easy to observe, such as by using convenient data or using surrogate markers. In essence, the streetlight effect is embraced due to its low-risk nature. In the long run, however, the streetlight effect can slow the rate of medical progress by leading us in unfruitful directions. In the second part of the chapter, we extend the discussion by interpreting the streetlight in a more literal sense, focusing on how physical capital influences the rate and direction of research. In general, physical capital, such as laboratories and equipment, is a crucial enabler in allowing science to be conducted. It functions as a rate-limiting factor, meaning that without certain equipment or physical resources, some research undertakings are necessarily impossible to complete.

  • An interpretation of focal point responses as non-additive beliefs

  • Aylit Tina Romm
  • Journal:
    Judgment and Decision Making / Volume 9 / Issue 5 / September 2014
    Published online by Cambridge University Press:
    01 January 2023, pp. 387-402
    • Article
      • You have access
      • Open access
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  • This paper provides a novel interpretation of focal point responses (0, 50, 100 percent) in terms of ambiguous beliefs dynamics that arise in new developments of decision theory such as Choquet expected utility theory. In particular, focal point responses that have been updated from nonfocal responses can be interpreted as non-additive beliefs that account for psychological bias. A focal point response of 100 that has been updated from a nonfocal response can be represented by a non-additive belief that has been updated according to the Overestimating Update Rule. A focal point response of zero that has been updated from a nonfocal response can be represented by a non-additive belief that has been updated according to the Underestimating Update Rule. Focal point responses given consistently over time are not subject to psychological bias, and can be represented by additive probability distributions. Estimation results show such a model to be a very good fit to the data.