arXiv:2211.08419
Participation Interfaces for Human-Centered AI
원문 초록
Emerging artificial intelligence (AI) applications often balance the preferences and impacts among diverse and contentious stakeholder groups. Accommodating these stakeholder groups during system design, development, and deployment requires tools for the elicitation of disparate system interests and collaboration interfaces supporting negotiation balancing those interests. This paper introduces interactive visual "participation interfaces" for Markov Decision Processes (MDPs) and collaborative ranking problems as examples restoring a human-centered locus of control.
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Advances in Collaborative Filtering and Ranking
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
Temporal Collaborative Ranking Via Personalized Transformer
SQL-Rank: A Listwise Approach to Collaborative Ranking
CoRanking: Collaborative Ranking with Small and Large Ranking Agents
A Joint Two-Phase Time-Sensitive Regularized Collaborative Ranking Model for Point of Interest Recommendation
토론
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