Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work

Jane Hsieh, Angie Zhang, Sajel Surati, Sijia Xie, Yeshua Ayala, Nithila Sathiya, Tzu-Sheng Kuo, Min Kyung Lee, Haiyi Zhu

TL;DR

Gig2Gether addresses data opacity and isolation in the gig economy by designing a cross-platform, worker-centered data-sharing tool. The authors develop and evaluate a prototype through a 7-day field study with 16 gig workers across three domains, demonstrating that experiential stories and financial data can foster mutual aid, self-reflection, and planning, while also suggesting pathways to inform safety and wage policies. The study contributes a design space, workflow-oriented metrics, and a prototype that integrates Story sharing, income/expense tracking, and a planner to connect workers with policymakers and advocates. This work has practical implications for empowering gig workers, enabling evidence-based policy discussions, and guiding future development of cross-domain, privacy-preserving data-sharing tools in the platform economy.

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.

Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work

TL;DR

Gig2Gether addresses data opacity and isolation in the gig economy by designing a cross-platform, worker-centered data-sharing tool. The authors develop and evaluate a prototype through a 7-day field study with 16 gig workers across three domains, demonstrating that experiential stories and financial data can foster mutual aid, self-reflection, and planning, while also suggesting pathways to inform safety and wage policies. The study contributes a design space, workflow-oriented metrics, and a prototype that integrates Story sharing, income/expense tracking, and a planner to connect workers with policymakers and advocates. This work has practical implications for empowering gig workers, enabling evidence-based policy discussions, and guiding future development of cross-domain, privacy-preserving data-sharing tools in the platform economy.

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.

Paper Structure

This paper contains 74 sections, 17 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Demands of Gig Work: Shared and Divergent Challenges Across Platforms
  4. Work Tracking: Individual Logging $\rightarrow$ Collective Support & Decision-making
  5. Gaps in Current Approaches to Gig Worker-Centered Data-Sharing for Policy
  6. Research Team & Positionality
  7. Design Space & Requirements for Worker-Centered Data-sharing Tools
  8. Target User/Worker Populations
  9. Design Requirement 1: Center Worker Needs & Goals for Advancing Policy
  10. DR 2: Facilitate Worker Collaboration & Cross-Stakeholder Resource Sharing
  11. Design Exploration of a Worker-Centered Datasharing Tool
  12. Early Prototyping: Low-Fidelity Sketches
  13. Iterative Pilot Testing with Workers
  14. Gig2Gether
  15. Exchanging Qualitative Stories
  16. ...and 59 more sections

Figures (17)

  • Figure 1: Initial Sketches -- (a) aligns to & , (b) accommodates & , (c) targets &
  • Figure 2: Web Versions of Mid-fidelity Wireframes
  • Figure 3: Overview of Gig2Gether Features for Before, After and Between Gigs
  • Figure 4: Petsitter-1's response to another strategy
  • Figure 5: Driver-1's Strategy: Self-Protecting from a Trespassing Passenger
  • ...and 12 more figures