PrivacyAkinator uses LLM-generated questions grounded in data-flow representations and a news-mined design space to help developers surface privacy decisions, yielding 47% more decisions identified in 73% less time than PRAM in a 24-person study.
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AI in education should be reframed as a relational design problem grounded in reciprocity and accountability to support learning with others and sustain communities and environments.
citing papers explorer
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PrivacyAkinator: Articulating Key Privacy Design Decisions by Answering LLM-Generated Multiple-choice Questions
PrivacyAkinator uses LLM-generated questions grounded in data-flow representations and a news-mined design space to help developers surface privacy decisions, yielding 47% more decisions identified in 73% less time than PRAM in a 24-person study.
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Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews
AI in education should be reframed as a relational design problem grounded in reciprocity and accountability to support learning with others and sustain communities and environments.