Rae, Andrew and Alexander, Robert David orcid.org/0000-0003-3818-0310 (2017) Forecasts or fortune-telling:when are expert judgements of safety risk valid? Safety science. pp. 156-165. ISSN 0925-7535
Abstract
Safety analysis frequently relies on human estimates of the likelihood of specific events. For this purpose, the opinions of experts are given greater weight than the opinions of non-experts. Combinations of individual judgements are given greater weight than judgements made by a lone expert. Various authors advocate specific techniques for eliciting and combining these judgements. All of these factors – the use of experts, the use of multiple opinions, and the use of elicitation and combination techniques – serve to increase subjective confidence in the safety analysis. But is this confidence justified? Do the factors increase the actual validity of the analysis in proportion to the increase in subjective confidence? In this paper, by means of a critical synthesis of evidence from multiple disciplines, we argue that it is plausible that expert judgement deserves special standing, but only for well understood local causal mechanisms. We also conclude that expert judgements can be improved by using appropriate elicitation techniques, including by combining judgement from multiple experts. There is, however, no evidence to suggest that fuzzy algorithms, neural networks, or any other form of complicated processing of expert judgement have any advantage over simple combination mechanisms.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Elsevier Ltd. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 22 Nov 2017 11:00 |
Last Modified: | 19 Mar 2025 00:07 |
Published Version: | https://doi.org/10.1016/j.ssci.2017.02.018 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.ssci.2017.02.018 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:124368 |