分析Reddit上公众对生成式AI的信任与不信任，揭示其演变规律。
In Generative AI We (Dis)Trust? Computational Analysis of Trust and Distrust in Reddit Discussions
- 基于多年Reddit数据构建信任计算框架
- 信任与不信任基本平衡，模型发布时有明显波动
- 技术性能和使用体验是主要影响因素，适合政策与产品设计参考
生成式人工智能（GenAI）已深刻影响人类生活。随着这些系统融入日常实践，理解公众对其信任程度对于负责任的采用与治理至关重要。以往关于AI信任的研究多源于心理学与人机交互领域，但缺乏大规模、计算化、长期性的信任与不信任测量方法。本文首次开展生成式AI的计算研究，利用2022–2025年跨39个子版块、共计230,576篇帖子的Reddit数据集。通过众包标注代表性样本，并结合分类模型实现分析扩展。研究发现，信任与不信任在时间上几乎持平，尽管信任略占优势，且在重大模型发布时出现显著变化。技术性能与可用性是主导维度，个人体验是最常见的态度成因。不同群体（如专家、伦理学者、普通用户）呈现独特信任模式。研究结果为大规模信任分析提供方法框架，并揭示公众对生成式AI认知的动态演变。
原文摘要 · Abstract (English)
The rise of generative AI (GenAI) has impacted many aspects of human life. As these systems become embedded in everyday practices, understanding public trust in them is also essential for responsible adoption and governance. Prior work on trust in AI has largely drawn from psychology and human-computer interaction, but there is a lack of computational, large-scale, and longitudinal approaches to measuring trust and distrust in GenAI and large language models (LLMs). This paper presents the first computational study of trust and distrust in GenAI, using a multi-year Reddit dataset (2022--2025) spanning 39 subreddits and 230,576 posts. Crowd-sourced annotations of a representative sample were combined with classification models to scale analysis. We find that trust and distrust are nearly balanced over time, although trust modestly outweighs distrust, with shifts around major model releases. Technical performance and usability dominate as dimensions, while personal experience is the most frequent reason shaping attitudes. Distinct patterns also emerge across trustors (e.g., experts, ethicists, and general users). Our results provide a methodological framework for large-scale trust analysis and insights into evolving public perceptions of GenAI.
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