A taxonomy of human-machine collaboration: capturing automation and technical autonomy
Journal
AI & Society
Type
journal article
Date Issued
2020-07-02
Author(s)
Abstract
Due to the ongoing advancements in technology, socio-technical collaboration has become increasingly prevalent. This poses challenges in terms of governance and accountability, as well as issues in various other fields. Therefore, it is crucial to famil- iarize decision-makers and researchers with the core of human–machine collaboration. This study introduces a taxonomy that enables identification of the very nature of human–machine interaction. A literature review has revealed that automation and technical autonomy are main parameters for describing and understanding such interaction. Both aspects must be carefully evaluated, as their increase has potentially far-reaching consequences. Hence, these two concepts comprise the taxonomy’s axes. Five levels of automation and five levels of technical autonomy are introduced below, based on the assumption that both automation and autonomy are gradual. The levels of automation were developed from existing approaches; those of autonomy were carefully derived from a review of the literature. The taxonomy’s use is also explained, as are its limitations and avenues for further research.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
LS - Business Enterprise - Law, Innovation and Risk
Refereed
Yes
Publisher
Springer
Volume
Online First
Start page
1
End page
12
Pages
12
Subject(s)
Division(s)
Eprints ID
260651
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