Participatory design with 20 Afghan women reveals that safe GenAI learning companions must prioritize privacy, cultural fit, and genuine learning support, with the process itself linked to higher aspirations and agency.
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5 Pith papers cite this work, alongside 8 external citations. Polarity classification is still indexing.
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Audit of ChatGPT, Copilot, Gemini and Perplexity finds ~16% of cited sources are AI-generated across 712 queries on politics, health and environment.
Analyses of labeled social media sentences and interpretations show 30% divergence in ethos and pathos, greater variability for charged content, and predictive power for audience attitudes toward the author.
Cultural zones explain variance in safety ratings beyond demographics across six datasets, with roughly 10% of items identified as culturally sensitive.
Neural network learning opacity stems from three dynamical complexity properties in training, rendering some sources of opacity irreducible.
citing papers explorer
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Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education
Participatory design with 20 Afghan women reveals that safe GenAI learning companions must prioritize privacy, cultural fit, and genuine learning support, with the process itself linked to higher aspirations and agency.
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Synthetic Sources?: Auditing Generative Search Engine Citations for Evidence of AI-Generated Sources
Audit of ChatGPT, Copilot, Gemini and Perplexity finds ~16% of cited sources are AI-generated across 712 queries on politics, health and environment.
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How Ethos and Pathos Appeals Resonate in Reader Interpretations of Social Media Messages
Analyses of labeled social media sentences and interpretations show 30% divergence in ethos and pathos, greater variability for charged content, and predictive power for audience attitudes toward the author.
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Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment
Cultural zones explain variance in safety ratings beyond demographics across six datasets, with roughly 10% of items identified as culturally sensitive.
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How Complexity Contributes to Learning Opacity in Machine Learning
Neural network learning opacity stems from three dynamical complexity properties in training, rendering some sources of opacity irreducible.