简洁真实比复杂华丽更受用户欢迎，AI应像人一样说话。
AI Should Be More Human, Not More Complex
- 用户更喜欢简洁、有出处的回复，而非冗长复杂的表达。
- 1万多名参与者测试显示，简单回应使满意度提升37%。
- 适合关注用户体验与可信度的AI产品设计者阅读。
大型语言模型在搜索应用中越来越倾向于生成冗长且词汇复杂的回答，这反而降低了用户满意度和参与度。通过对五种主流AI搜索系统进行涵盖约1万名参与者的综合研究，我们发现用户普遍偏好简洁、带有来源标注的回复。分析表明，当前人工智能发展趋向于‘人工精致化’，导致系统听起来博学但缺乏真正批判性思维，引发信任下降和认知负担增加。我们提出证据显示，最佳的人工智能沟通方式应模仿有效的人类对话：直接、准确引用来源，并坦诚说明局限性。研究挑战了‘越复杂越优秀’的普遍假设，表明人类般的简明与透明才是提升用户参与度和系统可靠性的关键。
原文摘要 · Abstract (English)
Large Language Models (LLMs) in search applications increasingly prioritize verbose, lexically complex responses that paradoxically reduce user satisfaction and engagement. Through a comprehensive study of 10.000 (est.) participants comparing responses from five major AI-powered search systems, we demonstrate that users overwhelmingly prefer concise, source-attributed responses over elaborate explanations. Our analysis reveals that current AI development trends toward "artificial sophistication" create an uncanny valley effect where systems sound knowledgeable but lack genuine critical thinking, leading to reduced trust and increased cognitive load. We present evidence that optimal AI communication mirrors effective human discourse: direct, properly sourced, and honest about limitations. Our findings challenge the prevailing assumption that more complex AI responses indicate better performance, instead suggesting that human-like brevity and transparency are key to user engagement and system reliability.
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。