Presenter/Author Information

J. Myšiak
J. D. Brown

Keywords

integrated water resources management, uncertainty analysis, scientific policy aid, policy analysis

Start Date

1-7-2006 12:00 AM

Abstract

Uncertainty pervades all aspects of environmental policy making. Numerous typologies and techniques have been developed to conceptualise, classify, assess (qualitatively and quantitatively), propagate, control, reduce and communicate uncertainty. Such assessments are a necessary but insufficient condition for reducing uncertainty in environmental decision making. In this paper we discuss how uncertainty is translated into decisions. Since this entails numerous value judgements and trade-offs which are sensitive to how policy problems are framed, we argue that perceptions of uncertainty cannot be viewed independently of the (quality of) the policy process that it intends to inform. Thus, uncertainty management should not be limited to the elicitation of preferences and value judgements under uncertainty. Rather, it should be embedded within policy making processes more generally, including learning, surfacing tacit assumptions and scrutinising beliefs and knowledge.

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Jul 1st, 12:00 AM

Environmental Policy Aid Under Uncertainty

Uncertainty pervades all aspects of environmental policy making. Numerous typologies and techniques have been developed to conceptualise, classify, assess (qualitatively and quantitatively), propagate, control, reduce and communicate uncertainty. Such assessments are a necessary but insufficient condition for reducing uncertainty in environmental decision making. In this paper we discuss how uncertainty is translated into decisions. Since this entails numerous value judgements and trade-offs which are sensitive to how policy problems are framed, we argue that perceptions of uncertainty cannot be viewed independently of the (quality of) the policy process that it intends to inform. Thus, uncertainty management should not be limited to the elicitation of preferences and value judgements under uncertainty. Rather, it should be embedded within policy making processes more generally, including learning, surfacing tacit assumptions and scrutinising beliefs and knowledge.