AI 模拟心理病人，这次不像 AI 了
心理治疗里有个难题：来访者常常说不清自己的痛苦，而现有的 AI 模拟病人会把话说得太清楚、太有条理，反而失真。这篇提出一个叫 Pandora 的框架，它不再只按病历生成回答，而是先模拟来访者当下的心理和关系状态，再结合这个人平时的说话习惯，最后才组织语言。结果在 115 个案例的测试里，它生成的表达更像真人，被评估者认为“像 AI”的比例只有 7.2%，而其他方法高达 43% 到 67%。这不是你明天能用的工具，但它意味着 AI 在心理咨询训练里，可能第一次能逼真地扮演一个“说不清自己”的来访者。
📄 原文摘要(英文)
Psychotherapy clients may experience distress before they can coherently describe it, and their expression changes with emotion, perceived safety, and trust. Large language model-based client simulators often rely on clinically organized case descriptions, which can encourage responses explaining the client's difficulties more clearly than their current understanding warrants. We propose Pandora, a psychotherapy client simulation framework that models how psychological experience becomes situated, individual expression. Pandora updates psychological and relational states in response to therapist interventions, constructs subjective appraisals and attributions, and plans response content and strategy. A separate expression planner combines these decisions with language patterns distilled from the client's utterances to guide linguistic realization. We evaluate Pandora against five baselines on 115 cases from four counseling and motivational interviewing datasets. It achieves the highest expression similarity and overall disclosure-alignment score among the compared systems. In a four-evaluator study of 45 matched disclosure items, Pandora receives AI-like judgments in 7.2% of ratings, compared with 43.3--67.2% for the baselines and 35.6% without expression planning. The ablation also reduces expression similarity. These results support explicit expression planning in client simulation to improve alignment with individual language patterns and reduce perceived AI-like expression in the evaluated setting.