A taxonomy of human–machine collaboration: capturing automation and technical autonomy

被引:0
作者
Monika Simmler
Ruth Frischknecht
机构
[1] University of St. Gallen,Law School
[2] University of St. Gallen,Institute for Systemic Management and Public Governance
来源
AI & SOCIETY | 2021年 / 36卷
关键词
Human–machine collaboration; Taxonomy; Automation; Autonomy;
D O I
暂无
中图分类号
学科分类号
摘要
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 familiarize 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.
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页码:239 / 250
页数:11
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