Data Probes as Boundary Objects for Technology Policy Design: Demystifying Technology for Policymakers and Aligning Stakeholder Objectives in Rideshare Gig Work
Angie Zhang, Rocita Rana, Alexander Boltz, Veena Dubal, Min Kyung Lee
摘要
Despite the evidence of harm that technology can inflict, commensurate policymaking to hold tech platforms accountable still lags. This is pertinent to app-based gig workers, where unregulated algorithms continue to dictate their work, often with little human recourse. While past HCI literature has investigated workers' experiences under algorithmic management and how to design interventions, rarely are the perspectives of stakeholders who inform or craft policy sought. To bridge this, we propose using data probes-interactive visualizations of workers' data that show the impact of technology practices on people-exploring them in 12 semistructured interviews with policy informers, (driver-)organizers, litigators, and a lawmaker in the rideshare space. We show how data probes act as boundary objects to assist stakeholder interactions, demystify technology for policymakers, and support worker collective action. We discuss the potential for data probes as training tools for policymakers, and considerations around data access and worker risks when using data probes.
• Human-centered computing → Human computer interaction (HCI).
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- Algorithmic Management Reimagined For Workers and By Workers: Centering Worker Well-Being in Gig WorkAngie Zhang, Alexander Boltz, Chun Wei Wang, Min Kyung LeeCHI 2022 · 被引用 166 次
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