Co-design workshops at Kiva show that organizational justice better captures employee concerns for recommender systems than distributional fairness alone and yields concrete monitoring metrics.
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A co-creation process for inferring and refining personal strivings from computer activity logs yields more representative goals and higher user agency than baselines in a 14-person week-long study.
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
A qualitative study of a provotype shows that adding transparency and control features to AI recommender interfaces helps users understand personalization, address filter bubble concerns, and build trust.
citing papers explorer
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Co-Designing Organizational Justice Indicators for Algorithmic Systems
Co-design workshops at Kiva show that organizational justice better captures employee concerns for recommender systems than distributional fairness alone and yields concrete monitoring metrics.
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"What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Use
A co-creation process for inferring and refining personal strivings from computer activity logs yields more representative goals and higher user agency than baselines in a 14-person week-long study.
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When and How AI Should Assist Brainstorming for AI Impact Assessment
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
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Rethinking User Empowerment in AI Recommender System: Innovating Transparent and Controllable Interfaces
A qualitative study of a provotype shows that adding transparency and control features to AI recommender interfaces helps users understand personalization, address filter bubble concerns, and build trust.