Interviews with 18 older adults show that AI safety interventions frequently disrupt emotional support-seeking, leading to calls for designs that respect users' pacing and preserve agency.
In:Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
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LLMs produce interpretive closure in 87.5% of ambiguous social scenarios through narrative alignment, reversal, or normative advice, with first-person perspectives increasing alignment tendencies.
citing papers explorer
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Designing with Tensions: Older Adults' Emotional Support-Seeking Under System-Level Constraints in Conversational AI
Interviews with 18 older adults show that AI safety interventions frequently disrupt emotional support-seeking, leading to calls for designs that respect users' pacing and preserve agency.
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What Did They Mean? How LLMs Resolve Ambiguous Social Situations across Perspectives and Roles
LLMs produce interpretive closure in 87.5% of ambiguous social scenarios through narrative alignment, reversal, or normative advice, with first-person perspectives increasing alignment tendencies.