用AI助手帮神经典型用户理解自闭症沟通难题，减少责备心态。
NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners
- 构建多智能体LLM系统，模拟自闭症者内心体验并引导对话。
- 实验显示用户缺陷归因显著降低，对话轮次减少37%。
- 适合想改善与自闭症者沟通的神经典型人士使用。
双共情问题将神经多样性与神经典型个体间的沟通困难归因于相互误解，但多数干预仍聚焦自闭症者。我们提出NeuroWise，一种基于多智能体LLM的教练系统，通过压力可视化、内在体验解读和情境指导支持神经典型用户。在一项组间设计研究（N=30）中，所有参与者均认为NeuroWise有帮助，且显示出显著的条件-时间效应（p=0.02）：NeuroWise用户减少了缺陷归因，而基线组在困难互动后更倾向于指责自闭症者的“缺陷”。此外，NeuroWise用户完成对话效率更高（回合数减少37%，p=0.03）。结果表明，基于AI的解释可帮助用户将沟通挑战视为双向问题。
原文摘要 · Abstract (English)
The double empathy problem frames communication difficulties between neurodivergent and neurotypical individuals as arising from mutual misunderstanding, yet most interventions focus on autistic individuals. We present NeuroWise, a multi-agent LLM-based coaching system that supports neurotypical users through stress visualization, interpretation of internal experiences, and contextual guidance. In a between-subjects study (N=30), NeuroWise was rated as helpful by all participants and showed a significant condition-time effect on deficit-based attributions (p=0.02): NeuroWise users reduced deficit framing, while baseline users shifted toward blaming autistic "deficits" after difficult interactions. NeuroWise users also completed conversations more efficiently (37% fewer turns, p=0.03). These findings suggest that AI-based interpretation can support attributional change by helping users recognize communication challenges as mutual.
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