让聊天机器人更像真人？用户自己设计形象比悄悄模仿更有效。
The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbots
- 让用户自定义角色形象，比后台自动模仿语言风格更能建立信任。
- 动态模仿用户语言反而降低满意度，且被评作不够自然，存在悖论。
- 适合关注情感陪伴、人机互动设计的研究者与产品团队参考。
生成式AI驱动着越来越多的陪伴型聊天机器人，但如何建立真实连接仍无定论。我们测试了两种路径：显性用户创作与隐性语言风格模仿。在一项预注册的3×2实验（N = 162）中，操控了用户控制的角色生成方式（无、预设、用户生成）和语言风格匹配（静态 vs. 动态适应）。结果显示，用户生成角色显著提升亲密度（ω² = .040, p = .013），而动态风格匹配在个性化和满意度上表现劣于静态匹配（d = 0.35, p = .009），且被评价为更不具适应性（t = 3.07, p = .003, d = 0.48）。我们称此为‘适应悖论’：当同步性被视为不连贯时，反而破坏了角色稳定性。为此提出‘稳定与可读性’解释：显性创作促进自然交互，而隐性模仿易引发认知失调。研究建议设计者应优先支持清晰、用户主导的个性化，限制风格突变，避免依赖不可见的模仿。
原文摘要 · Abstract (English)
Generative AI powers a growing wave of companion chatbots, yet principles for fostering genuine connection remain unsettled. We test two routes: visible user authorship versus covert language-style mimicry. In a preregistered 3x2 experiment (N = 162), we manipulated user-controlled avatar generation (none, premade, user-generated) and Language Style Matching (LSM) (static vs. adaptive). Generating an avatar boosted rapport ($ω^2$ = .040, p = .013), whereas adaptive LSM underperformed static style on personalization and satisfaction (d = 0.35, p = .009) and was paradoxically judged less adaptive (t = 3.07, p = .003, d = 0.48). We term this an Adaptation Paradox: synchrony erodes connection when perceived as incoherent, destabilizing persona. To explain, we propose a stability-and-legibility account: visible authorship fosters natural interaction, while covert mimicry risks incoherence. Our findings suggest designers should prioritize legible, user-driven personalization and limit stylistic shifts rather than rely on opaque mimicry.
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