AI 中文总结
研究探讨人机交流中情感模式与表达-感知不对称，通过虚拟现实实验，自主系统传递情感模式引发人类情绪，但机器监测通道沉默，揭示机器能动性在表达与感知上的不对称，为相关理论及设计提供启示。
AI 中文摘要
情感自适应系统越来越多地充当能够感知用户情绪并通过旨在改变情绪的事件做出回应的沟通者，形成情感闭环。这一设想假定机器的情感信息能被接收且其监测的身体通道能给出可理解的回复，而这两个假定很少同时得到验证。在一项有20名受试者的虚拟现实研究中，一个自主系统传递了六种基于经验得出的情感模式，同时记录人类在感受情绪、感受唤醒以及自主（皮肤电和心脏）活动方面的回复。结果显示，机器仅作为设计信息的发出者时，能可靠地引发强烈且有差异的情绪，然而机器本应读取的通道基本保持沉默。自我报告的唤醒没有变化，贝叶斯分析及等效性证据表明无影响；交感神经和心脏唤醒仅在最显著的事件时有变化，而非对最强烈的信息有反应；在个体内部，感受效价与两种身体指标均脱钩。这种效价-唤醒解离揭示了一种表达-感知不对称：机器能动性延伸到表达但非感知，闭环设计所调节的变量，其信息既不能可靠地改变也难以被读取。我们阐述了这一研究对机器能动性理论和情感自适应设计的启示。
英文摘要
Affect-adaptive systems increasingly act as communicators that sense a user's emotion and respond with events meant to change it, closing an affective loop. This vision assumes both that a machine's affective messages are received and that the bodily channel it monitors carries an intelligible reply-assumptions rarely tested together. In a within-subjects virtual-reality study (N = 20), an autonomous system delivered six empirically derived affective patterns-scripted emotional events distilled from 104 practitioners' (first responders') critical incidents-while we recorded the human reply across felt emotion, felt arousal, and autonomic (electrodermal and cardiac) activity. Acting only as an author of designed messages, the machine reliably evoked strong, differentiated emotions: valence fell sharply for every pattern (|dz| = 1.1-1.7), and the patterns produced distinguishable, individually classifiable signatures of anger, fear, and sadness, functioning as a vocabulary of machine-to-human affective messages. Yet the channel the machine would read stayed largely silent. Self-reported arousal did not change, with Bayesian and equivalence evidence for no effect; sympathetic and cardiac arousal moved only for the most perceptually salient events, not for the messages experienced as most powerful; and within individuals, felt valence was decoupled from both bodily registers. This valence-arousal dissociation reveals an expressive-sensing asymmetry: machine agency extends to expression but not perception, and closed-loop designs regulate on a variable their messages neither reliably move nor are legible in. We draw out implications for theories of machine agency and for affect-adaptive design.
