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Seeing What You Want to See: How Imprecise Uncertainty Ranges Enhance Motivated Reasoning

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  • Nathan F. Dieckmann
  • Robin Gregory
  • Ellen Peters
  • Robert Hartman

Abstract

In this article, we consider a novel criterion for evaluating representations of uncertainty ranges, namely, the extent to which a representation enhances motivated reasoning. In two studies, we show that perceptions of the distribution underlying ambiguous numerical ranges are affected by the motivations and worldviews of end users. This motivated reasoning effect remained after controlling for objective numeracy and fluid intelligence but was attenuated when the correct interpretation was made clear. We suggest that analysts and communicators explicitly consider the potential for motivated evaluation when evaluating uncertainty displays.

Suggested Citation

  • Nathan F. Dieckmann & Robin Gregory & Ellen Peters & Robert Hartman, 2017. "Seeing What You Want to See: How Imprecise Uncertainty Ranges Enhance Motivated Reasoning," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 471-486, March.
    • Handle: RePEc:wly:riskan:v:37:y:2017:i:3:p:471-486
    DOI: 10.1111/risa.12639
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    References listed on IDEAS

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    1. Schweitzer, Maurice E & Hsee, Christopher K, 2002. "Stretching the Truth: Elastic Justification and Motivated Communication of Uncertain Information," Journal of Risk and Uncertainty, Springer, vol. 25(2), pages 185-201, September.
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    6. Nathan F. Dieckmann & Robert Mauro & Paul Slovic, 2010. "The Effects of Presenting Imprecise Probabilities in Intelligence Forecasts," Risk Analysis, John Wiley & Sons, vol. 30(6), pages 987-1001, June.
    7. Nathan F. Dieckmann & Paul Slovic & Ellen M. Peters, 2009. "The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1473-1488, October.
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    Cited by:

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    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
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    7. van der Bles, Anne Marthe & van der Liden, Sander & Freeman, Alessandra L. J. & Mitchell, James & Galvao, Ana Beatriz & Spiegelhalter, David J., 2019. "Communicating uncertainty about facts, numbers, and science," EMF Research Papers 22, Economic Modelling and Forecasting Group.
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    9. Branden B. Johnson, 2019. "Experiments in Lay Cues to the Relative Validity of Positions Taken by Disputing Groups of Scientists," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1657-1674, August.
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