Large language model-based socio-emotional companions for children in welfare institutions: Attitudes, needs, and ethical implications

Abstract

This study, guided by a strengths-based perspective in positive psychology, explores children's attitudes toward and needs for large language model (LLM) based socio-emotional companions, considering how LLM-based chatbots might foster children's socio-emotional support. Using a mixed-methods design, we conducted questionnaire surveys (N = 43) and two rounds of in-depth interviews (N = 22) with children aged 10-18 residing in a welfare institution in Tibet. We examine their perceptions of artificial intelligence (AI) and expectations for an "AI smart friend". Findings indicated that: (1) The need for emotional companionship was urgent, with peer support serving as the primary resource (23 children reported turning to friends when feeling sad); (2) acceptance of AI companions is high (85% reported "somewhat want" or "very much want"), with expectations that AI would primarily provide academic tutoring and emotional support, especially as a proactive encourager (57% of interviewees favored an "encourager" persona); (3) trust is defined by clear ethical boundaries, with "no disclosure of secrets" forming the strongest consensus (mentioned by 37 participants), and many children noted that AI lacks the "warmth" and "emotion" of real humans. Overall, AI socio-emotional companions show potential in meeting children's emotional and learning needs, providing useful insights for the design of future AI support systems.

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