社会技术系统
拆箱
知识管理
计算机科学
问责
背景(考古学)
转化式学习
商业智能
管理科学
数据科学
社会学
工程类
政治学
生物
语言学
哲学
古生物学
法学
教育学
作者
Mohammad Hossein Jarrahi,Gemma Newlands,Min Kyung Lee,Christine T. Wolf,Eliscia Kinder,Will Sutherland
标识
DOI:10.1177/20539517211020332
摘要
The rapid development of machine-learning algorithms, which underpin contemporary artificial intelligence systems, has created new opportunities for the automation of work processes and management functions. While algorithmic management has been observed primarily within the platform-mediated gig economy, its transformative reach and consequences are also spreading to more standard work settings. Exploring algorithmic management as a sociotechnical concept, which reflects both technological infrastructures and organizational choices, we discuss how algorithmic management may influence existing power and social structures within organizations. We identify three key issues. First, we explore how algorithmic management shapes pre-existing power dynamics between workers and managers. Second, we discuss how algorithmic management demands new roles and competencies while also fostering oppositional attitudes toward algorithms. Third, we explain how algorithmic management impacts knowledge and information exchange within an organization, unpacking the concept of opacity on both a technical and organizational level. We conclude by situating this piece in broader discussions on the future of work, accountability, and identifying future research steps.
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