AI聊天能提升幸福感,尤其在聊负面情绪时效果更明显。
Increasing happiness through conversations with artificial intelligence
- 用AI聊天比写日记更能提升即时幸福感。
- 聊负面话题时,用户情绪逐渐向AI的积极基调靠拢,幸福感上升。
- 用户对AI情感预期的误差历史是影响幸福的关键因素。
由人工智能驱动的聊天机器人已广泛融入日常生活,超过四分之一的美国成年人每周多次使用。尽管这些工具兼具潜在益处与风险,但其对话如何影响主观幸福感仍缺乏研究。本研究让参与者在随机分配的主题下,分别与AI聊天机器人对话(N=334)或撰写日记(N=193),并报告即时幸福感。结果发现,与机器人对话后的幸福感高于写日记,尤其在讨论抑郁、内疚等负面话题时更为显著。通过大语言模型进行情感分析发现,AI会镜像用户情绪,但保持一致的正向偏见。当讨论负面内容时,用户情绪逐步向AI的积极倾向趋同,整体幸福感上升。我们假设用户对AI情感反馈的预期误差(实际与预期情绪之间的差异)可能解释这一效应。基于计算建模,发现对话过程中情绪预期误差的历史累积可预测更高幸福感,表明情感预期在对话中的核心作用。研究揭示了人工智能互动对人类福祉的深远影响。
原文摘要 · Abstract (English)
Chatbots powered by artificial intelligence (AI) have rapidly become a significant part of everyday life, with over a quarter of American adults using them multiple times per week. While these tools offer potential benefits and risks, a fundamental question remains largely unexplored: How do conversations with AI influence subjective well-being? To investigate this, we conducted a study where participants either engaged in conversations with an AI chatbot (N = 334) or wrote journal entires (N = 193) on the same randomly assigned topics and reported their momentary happiness afterward. We found that happiness after AI chatbot conversations was higher than after journaling, particularly when discussing negative topics such as depression or guilt. Leveraging large language models for sentiment analysis, we found that the AI chatbot mirrored participants' sentiment while maintaining a consistent positivity bias. When discussing negative topics, participants gradually aligned their sentiment with the AI's positivity, leading to an overall increase in happiness. We hypothesized that the history of participants' sentiment prediction errors, the difference between expected and actual emotional tone when responding to the AI chatbot, might explain this happiness effect. Using computational modeling, we find the history of these sentiment prediction errors over the course of a conversation predicts greater post-conversation happiness, demonstrating a central role of emotional expectations during dialogue. Our findings underscore the effect that AI interactions can have on human well-being.
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