Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes
Not on the map. Why?
Abstract (arXiv)
AI technologies continue to advance from digital assistants to assisted decision-making. However, designing AI remains a challenge given its unknown outcomes and uses. One way to expand AI design is by centering stakeholders in the design process. We conduct co-design sessions with gig workers to explore the design of gig worker-centered tools as informed by their driving patterns, decisions, and personal contexts. Using workers' own data as well as city-level data, we create probes -- interactive data visuals -- that participants explore to surface the well-being and positionalities that shape their work strategies. We describe participant insights and corresponding AI design considerations surfaced from data probes about: 1) workers' well-being trade-offs and positionality constraints, 2) factors that impact well-being beyond those in the data probes, and 3) instances of unfair algorithmic management. We discuss the implications for designing data probes and using them to elevate worker-centered AI design as well as for worker advocacy.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Mar 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 3; 2026: 1.
6 papers.
- 2025Secondary Stakeholders in AI: Fighting for, Brokering, and Navigating Agencycited by 3
- 2024The AI-DEC: A Card-based Design Method for User-centered AI Explanationscited by 2
- 2023Positive AI: Key Challenges in Designing Artificial Intelligence for Wellbeingcited by 1
- 2025FairFare: A Tool for Crowdsourcing Rideshare Data to Empower Labor Organizerscited by 1
- 2026The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotationcited by 1
- 2025FareShare: A Tool for Labor Organizers to Estimate Lost Wages and Contest Arbitrary AI and Algorithmic Deactivationscited by 0
- 2026The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation11 Feb 2026
- 2025Secondary Stakeholders in AI: Fighting for, Brokering, and Navigating Agency8 Jun 2025
- 2025FareShare: A Tool for Labor Organizers to Estimate Lost Wages and Contest Arbitrary AI and Algorithmic Deactivations13 May 2025
- 2025FairFare: A Tool for Crowdsourcing Rideshare Data to Empower Labor Organizers16 Feb 2025
- 2024The AI-DEC: A Card-based Design Method for User-centered AI Explanations26 May 2024
- 2023Positive AI: Key Challenges in Designing Artificial Intelligence for Wellbeing12 Apr 2023