区分自主与共情认知模型，揭示人类对AI反应差异
Mental Models of Autonomy and Sentience Shape Reactions to AI
- 通过情景实验分离自主与共情认知模型
- 共情模型显著提升道德考量和心智感知，自主模型增强威胁感
- 共情比自主更能改变人类对AI的整体反应
人工智能叙事常将自主性（自我管理能力）与共情性（感知与感受能力）混为一谈。自主执行任务的AI代理与能识别并表达情感的陪伴型AI可能分别激活自主与共情的认知模型，引发不同反应。为此，我们进行了三项预研（N=374）及四项预注册的情景实验（N=2,702），描述一个AI在自主、共情、两者兼具或皆无的条件下表现。激活共情模型比自主模型更显著提升整体心智感知（认知与情绪）和道德考量，但自主模型引发更高威胁感知；共情也增强了对自主性的感知。基于论文内元分析，共情平均而言对反应的影响大于自主。通过解耦不同认知模型，可更精确研究人机交互，优化拟人化AI与提示界面的设计。
原文摘要 · Abstract (English)
Narratives about artificial intelligence (AI) entangle autonomy, the capacity to self-govern, with sentience, the capacity to sense and feel. AI agents that perform tasks autonomously and companions that recognize and express emotions may activate mental models of autonomy and sentience, respectively, provoking distinct reactions. To examine this possibility, we conducted three pilot studies (N = 374) and four preregistered vignette experiments describing an AI as autonomous, sentient, both, or neither (N = 2,702). Activating a mental model of sentience increased general mind perception (cognition and emotion) and moral consideration more than autonomy, but autonomy increased perceived threat more than sentience. Sentience also increased perceived autonomy more than vice versa. Based on a within-paper meta-analysis, sentience changed reactions more than autonomy on average. By disentangling different mental models of AI, we can study human-AI interaction with more precision to better navigate the detailed design of anthropomorphized AI and prompting interfaces.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。