Latest revision as of 07:58, 2 February 2021

Abstract

Motivation - Automation can fail to deliver the target safety or productivity benefit as intended by those managers and designers advocating its introduction. In a safety critical domain this problem is of significance not only because the unexpected effects of automation might prevent its widespread usage but also because they might turn out to be a contributor to incident and accidents. Originality/value - Research on failures of automation to deliver the intended benefit has focused mainly on human automation interaction. This PhD research plan aims at characterizing decisions - taken under productive pressure - for those involved in the automation development process, to identify where and when the initial intention the automation is supposed to deliver can drift from the initial idea. Expected Finding - The objective is to develop Anti-Drift Principles to identify and compensate proactively for possible sources of drift in the development of new automation. Research Approach - The research is based on case study and is currently entering Year 2.

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The different versions of the original document can be found in:

• https://www.scienceopen.com/document_file/a698e114-5311-4083-b995-4fe3b1ba5294/ScienceOpen/384_Rozzi.pdf under the license https://creativecommons.org/licenses/by

• https://scienceopen.com/document?vid=65bdcdcd-5d59-4f20-abf8-c2f07f362210,

http://dx.doi.org/10.14236/ewic/ndm2009.63 under the license cc-by

• https://www.bcs.org/upload/pdf/ewic_ndm09_s4paper9.pdf,

https://core.ac.uk/download/pdf/9840291.pdf,

https://uhra.herts.ac.uk/handle/2299/10182,

http://uhra.herts.ac.uk/bitstream/handle/2299/10182/904850.pdf?sequence=1,

http://www.bcs.org/content/ConMediaFile/10984,

https://academic.microsoft.com/#/detail/324309153 under the license http://creativecommons.org/licenses/by/4.0/