Negative learning

Oppenheimer M, O'Neill BC, & Webster M (2008). Negative learning. Climatic Change 89 (1): 155-172. DOI:10.1007/s10584-008-9405-1.

Full text not available from this repository.

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.

Item Type: Article
Research Programs: Population and Climate Change (PCC)
Bibliographic Reference: Climatic Change; 89(1-2):155-172 [2008]
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 08:41
Last Modified: 18 Feb 2016 16:20
URI: http://pure.iiasa.ac.at/8574

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313