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Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes

arXiv 2303.03367 ↗First posted 6 Mar 2023cs.HCcited by 6

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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.

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Citing papers per year: 2023: 1; 2024: 1; 2025: 3; 2026: 1.

6 papers.