Vanderhaegen, F and Carsten, O (2017) Can dissonance engineering improve risk analysis of human–machine systems? Cognition, Technology & Work, 19 (1). pp. 1-12. ISSN 1435-5558
Abstract
The paper discusses dissonance engineering and its application to risk analysis of human–machine systems. Dissonance engineering relates to sciences and technologies relevant to dissonances, defined as conflicts between knowledge. The richness of the concept of dissonance is illustrated by a taxonomy that covers a variety of cognitive and organisational dissonances based on different conflict modes and baselines of their analysis. Knowledge control is discussed and related to strategies for accepting or rejecting dissonances. This acceptability process can be justified by a risk analysis of dissonances which takes into account their positive and negative impacts and several assessment criteria. A risk analysis method is presented and discussed along with practical examples of application. The paper then provides key points to motivate the development of risk analysis methods dedicated to dissonances in order to identify the balance between the positive and negative impacts and to improve the design and use of future human–machine system by reinforcing knowledge.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017, Springer-Verlag London. This is a post-peer-review, pre-copyedit version of an article published in Cognition, Technology & Work. The final authenticated version is available online at: https://doi.org/10.1007/s10111-017-0405-7 |
Keywords: | Dissonance engineering; Risk analysis; Conflict evaluation; Behavioural conflict; Knowledge evolution |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Mar 2018 16:19 |
Last Modified: | 21 Mar 2018 16:19 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s10111-017-0405-7 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128736 |