''It Hasn’t Lived in Our Society”: Investigating Cultural Sensitivity in LLM Chatbots for Emotional Support

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Authors: Sarah Aldaweesh, Ghzal Alelsheikh, Falwah Alhamed, Max Van Kleek, Nigel Shadbolt
Cited by: 1
References: 120

Abstract

Large Language Models (LLMs) offer potential benefits for increasing access to digital well-being support, yet their application raises important questions about risks and responsible implementation. This paper examines a critical, often overlooked, dimension of LLM safety: cultural and social alignment in underrepresented contexts. We investigate how LLM-mediated emotional support can be adapted for a specific cultural setting, using Saudi Arabia as a case study. We present CSESC, a Culturally Sensitive Emotional Support Chatbot, developed as a technology probe to explore user perceptions of culturally sensitive responses. Our adaptation process was grounded in emotional support frameworks and guided by multicultural guidelines and local expertise. User evaluations demonstrate that cultural alignment enhances users’ sense of relatedness, while also surfacing tensions between empathy and sociocultural norms. We discuss the notion of “minimum cultural alignment,” contributing to HCI literature on culturally responsive LLM design and broadening the understanding of LLM safety.

Fields of Study & Subjects

AI in Service Interactions Digital Mental Health Interventions Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–20
Publication date
13 April 2026