Designing with Culture: How Social Norms Shape Trust and Preference in Health Chatbots

Fuente: arXiv
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Autores principales: Wadhwa, Arpita, Vashistha, Aditya, Jain, Mohit
Formato: Preprint
Publicado: 2025
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author Wadhwa, Arpita
Vashistha, Aditya
Jain, Mohit
author_facet Wadhwa, Arpita
Vashistha, Aditya
Jain, Mohit
contents AI-driven chatbots are increasingly used to support community health workers (CHWs) in developing regions, yet little is known about how cultural framings in chatbot design shape trust in collectivist contexts where decisions are rarely made in isolation. This paper examines how CHWs in rural India responded to chatbots that delivered identical health content but varied in one specific cultural lever -- social norms. Through a mixed-methods study with 61 ASHAs who compared four normative framings -- neutral, descriptive, narrative identity, and injunctive authority -- we (1) analyze how framings influence preferences and trust, and (2) compare effects across low- and high-ambiguity scenarios. Results show that narrative framings were most preferred but encouraged uncritical overreliance, while authority framings were least preferred yet supported calibrated trust. We conclude with design recommendations for dynamic framing strategies that adapt to context and argue for calibrated trust -- following correct advice and resisting incorrect advice -- as a critical evaluation metric for safe, culturally-grounded AI.
format Preprint
id arxiv_https___arxiv_org_abs_2509_15575
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Designing with Culture: How Social Norms Shape Trust and Preference in Health Chatbots
Wadhwa, Arpita
Vashistha, Aditya
Jain, Mohit
Human-Computer Interaction
AI-driven chatbots are increasingly used to support community health workers (CHWs) in developing regions, yet little is known about how cultural framings in chatbot design shape trust in collectivist contexts where decisions are rarely made in isolation. This paper examines how CHWs in rural India responded to chatbots that delivered identical health content but varied in one specific cultural lever -- social norms. Through a mixed-methods study with 61 ASHAs who compared four normative framings -- neutral, descriptive, narrative identity, and injunctive authority -- we (1) analyze how framings influence preferences and trust, and (2) compare effects across low- and high-ambiguity scenarios. Results show that narrative framings were most preferred but encouraged uncritical overreliance, while authority framings were least preferred yet supported calibrated trust. We conclude with design recommendations for dynamic framing strategies that adapt to context and argue for calibrated trust -- following correct advice and resisting incorrect advice -- as a critical evaluation metric for safe, culturally-grounded AI.
title Designing with Culture: How Social Norms Shape Trust and Preference in Health Chatbots
topic Human-Computer Interaction
url https://arxiv.org/abs/2509.15575