Negative Learning
Michael Oppenheimer¹, Brian C. O’Neill², and Mort Webster³

¹Woodrow Wilson School, Princeton University, USA
²Population and Climate Change Program, IIASA
³ Department of Public Policy University of North Carolina at Chapel Hill, USA

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 has 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. We suggest approaches to scientific assessment and decision making that could mitigate the problem.

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Last updated: 12 Feb 2007