Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work
🤖 AI Summary
Platformized labor exacerbates structural challenges for gig workers—including data opacity, social isolation, and inadequate social protections. To address these, we propose a worker-centered, lightweight collaborative data-sharing framework enabling voluntary contributions of experiential and aggregate data to support cross-platform mutual aid, financial reflection, algorithmic co-governance, and policy advocacy. Through a 7-day mixed-methods field study with 16 multi-platform workers, participatory design workshops, and collaborative log analysis, we demonstrate that this approach significantly enhances mutual aid capacity and financial planning awareness, while surfacing deeper demands for algorithmic auditing and institutional policy reform. Our work pioneers a data literacy pathway that systematically transforms individual narratives into collective action resources—bridging critical gaps between data capability, labor solidarity, and policy influence.
Application Category
📝 Abstract
The wide adoption of platformized work has generated remarkable advancements in the labor patterns and mobility of modern society. Underpinning such progress, gig workers are exposed to unprecedented challenges and accountabilities: lack of data transparency, social and physical isolation, as well as insufficient infrastructural safeguards. Gig2Gether presents a space designed for workers to engage in an initial experience of voluntarily contributing anecdotal and statistical data to affect policy and build solidarity across platforms by exchanging unifying and diverse experiences. Our 7-day field study with 16 active workers from three distinct platforms and work domains showed existing affordances of data-sharing: facilitating mutual support across platforms, as well as enabling financial reflection and planning. Additionally, workers envisioned future use cases of data-sharing for collectivism (e.g., collaborative examinations of algorithmic speculations) and informing policy (e.g., around safety and pay), which motivated (latent) worker desiderata of additional capabilities and data metrics. Based on these findings, we discuss remaining challenges to address and how data-sharing tools can complement existing structures to maximize worker empowerment and policy impact.
Problem
Research questions and friction points this paper is trying to address.
Enhancing data transparency for gig workers
Reducing social isolation among gig workers
Improving infrastructural safeguards in gig work
Innovation
Methods, ideas, or system contributions that make the work stand out.
Data-sharing platform for gig workers
Voluntary contribution of anecdotal data
Enhancing policy and worker solidarity
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