Work of the Unemployed: An inquiry into individuals’ experience of data usage in public services and possibilities for their agency
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Work of the Unemployed
Forlagets udgivne version, 2,35 MB, PDF-dokument
Public services increasingly presume a new and more active role for individuals to play in datafied society. While design efforts increasingly attempt to include stakeholders, such attempts are often limited to professional perspectives. Little is known about how individuals who are subject to these solutions experience the increasing use of data about them. One example of public services is job placement. Taking design fiction as our approach, we invited individuals enrolled in job placement (n=20) to reflect on the gwork of the unemployed', a fictive scenario where individuals make themselves eligible for support through sharing data. The fiction addresses power dynamics. The study shows how approaches, such as design fiction, are effective at including marginalized communities through changing the conditions for design. Showcasing the fictional outlook, and how the gdesign experience' can be disempowering if not qualified through a deeper critique, the paper contributes to agendas on design justice.
|DIS 2021 - Proceedings of the 2021 ACM Designing Interactive Systems Conference : Nowhere and Everywhere
|Association for Computing Machinery
|Udgivet - 2021
|2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere, DIS 2021 - Virtual, Online, USA
Varighed: 28 jun. 2021 → 2 jul. 2021
|2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere, DIS 2021
|28/06/2021 → 02/07/2021
|ACM Special Interest Group on Computer-Human Interaction (SIGCHI)
We thank all the individuals that were involved in the study for their engaged participation in the focus groups. We also extend our appreciation to the caseworkers and job centers that invited us to ethnographically study their practices, which has been the foundation for this work as part of the CompArt research project 2015-2018 supported by the Velux Foundations (award number 33295). Colleagues in the ECSCW community generously provided feedback on the first iteration of the fictional demo jobnettrace. Finally, we are indebted to Brit Winthereik and Irina Shklovski for discussing with us the nature of data – as well as Maria Menendez-Blanco, Thomas T Hildebrandt, Asbjørn Ammitzbøll Flügge, Geraldine Fitz-patrick, Marisa Cohn, Anette C. M. Petersen, and Tariq Andersen and the entire EcoKnow team that helped shape our ideas. This work has been supported by the Innovation Fund Denmark (award number 7050-00034A).
© 2021 ACM.
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