Researchers created a stigma-aware WhatsApp chatbot for menstrual health education in Pakistan through co-design workshops and a two-week deployment, yielding insights on its use for challenging taboos alongside tensions around trust and cultural explanations.
Rishadur Rahman, Nafis Irtiza Tripto, Mohammed Eunus Ali, Sajid Hasan Apon, and Rifat Shahriyar
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Structural mental models of AI writing assistants improve system understanding and usability but result in more grammatical errors in user writing compared to functional models.
This paper defines six dimensions of notification message quality, surveys LLM improvements over templates with reported CTR gains of 8-14.5%, and introduces a decision framework for when LLM generation is the binding constraint.
Deception in generative AI is subtle and normalized through defaults and interactions, with users often complicit, calling for friction, awareness, and regulatory approaches to protect users.
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Designing Around Stigma: Human-Centered LLMs for Menstrual Health
Researchers created a stigma-aware WhatsApp chatbot for menstrual health education in Pakistan through co-design workshops and a two-week deployment, yielding insights on its use for challenging taboos alongside tensions around trust and cultural explanations.
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From Use to Oversight: How Mental Models Influence User Behavior and Output in AI Writing Assistants
Structural mental models of AI writing assistants improve system understanding and usability but result in more grammatical errors in user writing compared to functional models.
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LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging
This paper defines six dimensions of notification message quality, surveys LLM improvements over templates with reported CTR gains of 8-14.5%, and introduces a decision framework for when LLM generation is the binding constraint.
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Exploring the "Banality" of Deception in Generative AI
Deception in generative AI is subtle and normalized through defaults and interactions, with users often complicit, calling for friction, awareness, and regulatory approaches to protect users.