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Why Hindsight Can Damage Foresight

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  • Paul Goodwin

Abstract

Goodwin defines hindsight bias and gives examples, examines its psychological basis, shows how it may interfere with the forecasting process, and suggests ways it might be at least partly overcome. Copyright International Institute of Forecasters, 2010

Suggested Citation

  • Paul Goodwin, 2010. "Why Hindsight Can Damage Foresight," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 17, pages 5-7, Spring.
    • Handle: RePEc:for:ijafaa:y:2010:i:17:p:5-7
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    Cited by:

    1. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.
    2. Haegeman, Karel & Marinelli, Elisabetta & Scapolo, Fabiana & Ricci, Andrea & Sokolov, Alexander, 2013. "Quantitative and qualitative approaches in Future-oriented Technology Analysis (FTA): From combination to integration?," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 386-397.
    3. Beth Coulthard & John Mallett & Brian Taylor, 2020. "Better Decisions for Children with “Big Data”: Can Algorithms Promote Fairness, Transparency and Parental Engagement?," Societies, MDPI, vol. 10(4), pages 1-16, December.
    4. Hansen, Mette Sanne & Rasmussen, Lauge Baungaard & Jacobsen, Peter, 2016. "Interactive foresight simulation," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 214-227.

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