Climatic Change

, Volume 89, Issue 1–2, pp 155–172 | Cite as

Negative learning

  • Michael Oppenheimer
  • Brian C. O’Neill
  • Mort Webster
Open Access
Article

Abstract

New technical information may lead to scientific beliefs that diverge over time from the a posteriori right answer. We call this phenomenon, which is particularly problematic in the global change arena, negative learning. Negative learning may have affected policy in important cases, including stratospheric ozone depletion, dynamics of the West Antarctic ice sheet, and population and energy projections. We simulate negative learning in the context of climate change with a formal model that embeds the concept within the Bayesian framework, illustrating that it may lead to errant decisions and large welfare losses to society. Based on these cases, we suggest approaches to scientific assessment and decision making that could mitigate the problem. Application of the tools of science history to the study of learning in global change, including critical examination of the assessment process to understand how judgments are made, could provide important insights on how to improve the flow of information to policy makers.

Supplementary material

10584_2008_9405_MOESM1_ESM.doc (2 mb)
ESM 1 (DOC 1.95 MB)

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Copyright information

© The Author(s) 2008

Authors and Affiliations

  • Michael Oppenheimer
    • 1
    • 2
  • Brian C. O’Neill
    • 3
    • 4
  • Mort Webster
    • 5
  1. 1.Woodrow Wilson School of Public and International AffairsPrinceton UniversityPrincetonUSA
  2. 2.Department of GeosciencesPrinceton UniversityPrincetonUSA
  3. 3.International Institute for Applied Systems AnalysisLaxenburgAustria
  4. 4.Institute for the Study of Society and EnvironmentNational Center for Atmospheric ResearchBoulderUSA
  5. 5.MIT Joint Program on the Science and Policy of Global ChangeMassachusetts Institute of TechnologyCambridgeUSA

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