大模型正在让人类表达和思维趋于单一，威胁集体创造力。
The Homogenizing Effect of Large Language Models on Human Expression and Thought
- 分析多学科证据，揭示大模型如何复制并强化主流表达模式
- 指出模型训练数据与广泛使用导致语言和思维趋同
- 警示认知多样性丧失对创新和适应力的潜在危害
认知多样性体现在语言、视角和推理方式的差异中，是创造力和集体智能的基础，源于文化、历史和个体经验。然而，随着大型语言模型（LLMs）深度嵌入日常生活，它们可能标准化语言与推理方式。本文综合语言学、心理学、认知科学与计算机科学的证据，表明大模型反映并强化主流风格，同时边缘化其他声音和思维方式。其设计与广泛使用通过复制训练数据中的模式，并在人们跨场景依赖同一模型时放大趋同效应。若不加控制，这种同质化将削弱驱动集体智能与适应性的认知多样性。
原文摘要 · Abstract (English)
Cognitive diversity, reflected in variations of language, perspective, and reasoning, is essential to creativity and collective intelligence. This diversity is rich and grounded in culture, history, and individual experience. Yet as large language models (LLMs) become deeply embedded in people's lives, they risk standardizing language and reasoning. We synthesize evidence across linguistics, psychology, cognitive science, and computer science to show how LLMs reflect and reinforce dominant styles while marginalizing alternative voices and reasoning strategies. We examine how their design and widespread use contribute to this effect by mirroring patterns in their training data and amplifying convergence as all people increasingly rely on the same models across contexts. Unchecked, this homogenization risks flattening the cognitive landscapes that drive collective intelligence and adaptability.
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