Hands on the Wheel: Navigating Algorithmic Management and Uber Drivers' Autonomy

With the rise of big data and networking capabilities, information systems can now automate management practices and perform complex tasks that were previously the responsibility of middle or upper management. These new practices, known as “algorithmic management,� have been applied by ride-hailing platforms such as Uber, whose business model is dependent on overseeing, managing, and controlling myriads of self-employed workers. This study seeks to understand this phenomenon from an information systems management perspective, highlighting the inherent paradox between workers’ sense of autonomy and these systems’ need of control. The paper offers a conceptualization of algorithmic management and employs interviews with Uber drivers and forum data to identify a series of mechanisms that drivers use to regain their autonomy under algorithmic management, including guessing, resisting, switching, and gaming the Uber system.