"At the end of the day, I am accountable": Gig Workers' Self-Tracking for Multi-Dimensional Accountability Management

March 28, 2024 Β· Declared Dead Β· πŸ› International Conference on Human Factors in Computing Systems

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Authors Rie Helene Hernandez, Qiurong Song, Yubo Kou, Xinning Gui arXiv ID 2403.19436 Category cs.HC: Human-Computer Interaction Citations 19 Venue International Conference on Human Factors in Computing Systems Last Checked 4 months ago
Abstract
Tracking is inherent in and central to the gig economy. Platforms track gig workers' performance through metrics such as acceptance rate and punctuality, while gig workers themselves engage in self-tracking. Although prior research has extensively examined how gig platforms track workers through metrics -- with some studies briefly acknowledging the phenomenon of self-tracking among workers -- there is a dearth of studies that explore how and why gig workers track themselves. To address this, we conducted 25 semi-structured interviews, revealing how gig workers self-tracking to manage accountabilities to themselves and external entities across three identities: the holistic self, the entrepreneurial self, and the platformized self. We connect our findings to neoliberalism, through which we contextualize gig workers' self-accountability and the invisible labor of self-tracking. We further discuss how self-tracking mitigates information and power asymmetries in gig work and offer design implications to support gig workers' multi-dimensional self-tracking.
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