Youth on Character.AI use chatbots for emotional restoration, creative exploration, and identity transformation, yielding a new three-intent framework and seven-archetype taxonomy from Discord discourse analysis.
Stakeholder Participation for Responsible AI Development: Disconnects Between Guidance and Current Practice
6 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 6representative citing papers
Thematic analysis of 43 AI contestation cases, using Bovens's relational accountability model, produces categories of demands from below, institutional pushback, outcomes, and contextual factors shaping effective contestation.
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
AI accountability efforts are undermined by five decoys that create illusions of progress while co-constituting the extractive political economy of the AI Project.
Proposes applying social choice theory as a modeling language and axiomatic tool for incorporating collective input across the ML development pipeline.
Mainstream conversational models show escalating affective misalignments and ethical guidance failures during staged emotional trajectories, organized into a taxonomy of interactional breakdowns.
citing papers explorer
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Restoration, Exploration and Transformation: How Youth Engage Character.AI Chatbots for Feels, Fun and Finding themselves
Youth on Character.AI use chatbots for emotional restoration, creative exploration, and identity transformation, yielding a new three-intent framework and seven-archetype taxonomy from Discord discourse analysis.
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Push and Pushback in Contesting AI: Demands for and Resistance to Accountability
Thematic analysis of 43 AI contestation cases, using Bovens's relational accountability model, produces categories of demands from below, institutional pushback, outcomes, and contextual factors shaping effective contestation.
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Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
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Reckoning with the Political Economy of AI: Avoiding Decoys in Pursuit of Accountability
AI accountability efforts are undermined by five decoys that create illusions of progress while co-constituting the extractive political economy of the AI Project.
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AI of the People, by the People, for the People: A Social Choice Approach to Collective Control of Artificial Intelligence
Proposes applying social choice theory as a modeling language and axiomatic tool for incorporating collective input across the ML development pipeline.
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Breakdowns in Conversational AI: Interactional Failures in Emotionally and Ethically Sensitive Contexts
Mainstream conversational models show escalating affective misalignments and ethical guidance failures during staged emotional trajectories, organized into a taxonomy of interactional breakdowns.