Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866913682813878272 |
|---|---|
| author | Hsieh, Jane Zhang, Angie Surati, Sajel Xie, Sijia Ayala, Yeshua Sathiya, Nithila Kuo, Tzu-Sheng Lee, Min Kyung Zhu, Haiyi |
| author_facet | Hsieh, Jane Zhang, Angie Surati, Sajel Xie, Sijia Ayala, Yeshua Sathiya, Nithila Kuo, Tzu-Sheng Lee, Min Kyung Zhu, Haiyi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_04482 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work Hsieh, Jane Zhang, Angie Surati, Sajel Xie, Sijia Ayala, Yeshua Sathiya, Nithila Kuo, Tzu-Sheng Lee, Min Kyung Zhu, Haiyi Human-Computer Interaction 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. |
| title | Gig2Gether: Data-sharing to Empower, Unify and Demystify Gig Work |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2502.04482 |