References in Use (and abuse) of expert elicitation in support of decision making for public policy - GCIS

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reference : Use (and abuse) of expert elicitation in support of decision making for public policy

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Use (and abuse) of expert elicitation in support of decision making for public policy

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reftype	Journal Article
Abstract	The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making.
Author	Morgan, M. Granger
DOI	10.1073/pnas.1319946111
Date	May 20, 2014
Issue	20
Journal	Proceedings of the National Academy of Sciences of the United States of America
Pages	7176-7184
Title	Use (and abuse) of expert elicitation in support of decision making for public policy
Volume	111
Year	2014

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_record_number	21386
_uuid	42c619a3-768b-4a22-9dd6-73b52af9426c