Cross-cultural survey of 4,641 participants shows LLM emotional support adoption varies widely by country and demographics, with socioeconomic status as strongest predictor of trust and use, and English-speaking nations more accepting than others in Europe.
Jung, Nicola Dell, Deborah Estrin, and James A
9 Pith papers cite this work. Polarity classification is still indexing.
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Proposes affective safety as a distinct class of AI harms with a taxonomy of self-alienation, bias, and relational harms, arguing that existing safety frameworks address it narrowly or not at all and calling for dedicated approaches focused on cumulative and identity-level effects.
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
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.
Twitch third-party developers’ Discord support-seeking is highly Twitch-dependent platform labor, worsened by Discord–Twitch switching, and needs bridge roles to formal support.
Larger Mastodon instances develop more extensive, topically diverse rules that are less readable, with consistent focus on problematic content and limited federation effects.
LLM assistance shortens idea-generation periods and reduces creative moments during programming tasks while yielding solutions with comparable idea counts and greater functional correctness.
An interactive public hammock captures and replays biodata as embodied traces, with a field study of ten users indicating it fosters anonymous connection and appreciation for shared vitality.
A new 200-prompt benchmark with age-group splits and a 0-5 refusal scale finds that even top LLMs are unsafe on 5-28% of child-facing adversarial prompts, with open-weight models performing worst.
citing papers explorer
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From Chatbots to Confidants: A Cross-Cultural Study of LLM Adoption for Emotional Support
Cross-cultural survey of 4,641 participants shows LLM emotional support adoption varies widely by country and demographics, with socioeconomic status as strongest predictor of trust and use, and English-speaking nations more accepting than others in Europe.
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Affective AI Safety: The Missing Piece in LLM Safety
Proposes affective safety as a distinct class of AI harms with a taxonomy of self-alienation, bias, and relational harms, arguing that existing safety frameworks address it narrowly or not at all and calling for dedicated approaches focused on cumulative and identity-level effects.
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Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
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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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Twitch Third-Party Developers' Support Seeking and Provision Practices on Discord
Twitch third-party developers’ Discord support-seeking is highly Twitch-dependent platform labor, worsened by Discord–Twitch switching, and needs bridge roles to formal support.
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Federating Governance: How Community Rules Scale with Mastodon Instances
Larger Mastodon instances develop more extensive, topically diverse rules that are less readable, with consistent focus on problematic content and limited federation effects.
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"Like Taking the Path of Least Resistance": Exploring the Impact of LLM Interaction on the Creative Process of Programming
LLM assistance shortens idea-generation periods and reduces creative moments during programming tasks while yielding solutions with comparable idea counts and greater functional correctness.
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HeartSway: Exploring Biodata as Poetic Traces in Public Space
An interactive public hammock captures and replays biodata as embodied traces, with a field study of ten users indicating it fosters anonymous connection and appreciation for shared vitality.
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Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions
A new 200-prompt benchmark with age-group splits and a 0-5 refusal scale finds that even top LLMs are unsafe on 5-28% of child-facing adversarial prompts, with open-weight models performing worst.