helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
Does workers' career experience affect how much they value positive reviews?Fairness, Bias, and Research Governance / Data Labor, Crowdsourced Annotation, and Platform Gig Fairness
Does workers' career experience affect how much they value positive reviews?
Similar questions
helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
What specific forms of human labor are involved in AI system production and maintenance?CSCW '24The Work of AI: Mapping Human Labour in the AI Pipeline
helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
How is human labor distributed across the global AI supply chain, and what inequalities exist?CSCW '24The Work of AI: Mapping Human Labour in the AI Pipeline
helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
How does invisible labor (e.g., emotional labor) affect AI systems' value and social impact?CSCW '24The Work of AI: Mapping Human Labour in the AI Pipeline
helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
How do consumers define and describe fairness in tipping behavior on food delivery platforms, and how does this differ from traditional non-technical media environments?helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
What role do food delivery platform companies play in consumers' evaluations of fairness?helpResearch questionData Labor, Crowdsourced Annotation, and Platform Gig Fairness
How can simple user click operations guide deep neural network attention distributions to reduce bias?IUI '23Efficient Human-in-the-loop System for Guiding DNNs Attention
Related papers
CHI 2024
Perceptions of Fairness in Technology-Mediated Marketplaces
Andrew Chong, Ji Su Yoo, Coye Cheshire
CHI 2022
How Much Do Platform Workers Value Reviews? An Experimental Method
David M Holtz, Liane Scult, Siddharth Suri
CHI 2021
It's About Time: A View of Crowdsourced Data Before and During the Pandemic
Evgenia Christoforou, Pinar Barlas, Jahna Otterbacher