计算机科学
工作(物理)
背景(考古学)
比例(比率)
数据科学
软件
知识管理
工程类
机械工程
古生物学
物理
量子力学
生物
程序设计语言
作者
Min Kyung Lee,Daniel Kusbit,Evan Metsky,Laura Dabbish
标识
DOI:10.1145/2702123.2702548
摘要
Software algorithms are changing how people work in an ever-growing number of fields, managing distributed human workers at a large scale. In these work settings, human jobs are assigned, optimized, and evaluated through algorithms and tracked data. We explore the impact of this algorithmic, data-driven management on human workers and work practices in the context of Uber and Lyft, new ridesharing services. Our findings from a qualitative study describe how drivers responded when algorithms assigned work, provided informational support, and evaluated their performance, and how drivers used online forums to socially make sense of the algorithm features. Implications and future work are discussed.
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