Now showing items 4-6 of 54988

    • Using collective dialogues and AI to find common ground between Israeli and Palestinian peacebuilders 

      Konya, Andrew; Thorburn, Luke; Almasri, Wasim; Leshem, Oded Adomi; Procaccia, Ariel; e.a. (ACM|The 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025-06-23)
      A growing body of work has shown that AI-assisted methods — leveraging large language models, social choice methods, and collective dialogues — can help navigate polarization and surface common ground in controlled lab ...
    • Recourse, Repair, Reparation, & Prevention: A Stakeholder Analysis of AI Supply Chains 

      Hopkins, Aspen; Struckman, Isabella; Klyman, Kevin; Silbey, Susan S. (ACM|The 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025-06-23)
      The AI industry is exploding in popularity, with increasing attention to potential harms and unwanted consequences. In the current digital ecosystem, AI deployments are often the product of AI supply chains (AISC): networks ...
    • When to Ask a Question: Understanding Communication Strategies in Generative AI Tools 

      Park, Charlotte; Donahue, Kate; Raghavan, Manish (ACM|Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization, 2025-06-12)
      Generative AI tools (GAITs) fundamentally differ from traditional machine learning tools in that they allow users to provide as much or as little information as they choose in their inputs. This flexibility often leads ...