Researchers analyzed 35 studies on children's interactions with large language model (LLM) chatbots, identifying human-like persona construction, adaptive scaffolding, supportive companionship, and non-human embodied design as drivers of anthropomorphism, where children attribute human characteristics to chatbots. These interactions can lead to outcomes such as paradoxical social and moral responses, dual consciousness, and attributing human narratives to conversation breakdowns. The findings can inform the design and development of LLM chatbots for children's well-being. AI summary
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