Data Probes as Boundary Objects for Technology Policy Design: Demystifying Technology for Policymakers and Aligning Stakeholder Objectives in Rideshare Gig Work

要旨

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 semi-structured 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.

著者
Angie Zhang
University of Texas at Austin, Austin, Texas, United States
Rocita Rana
University of Texas at Austin, Austin, Texas, United States
Alexander Boltz
University of Washington, Seattle, Washington, United States
Veena Dubal
University of California, Irvine, Irvine, California, United States
Min Kyung Lee
University of Texas at Austin, Austin, Texas, United States
論文URL

doi.org/10.1145/3613904.3642000

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Governance and Public Policies

319
5 件の発表
2024-05-15 20:00:00
2024-05-15 21:20:00