Contemporary artificial intelligence research has been organized around two dominant ambitions: productivity, which treats AI systems as tools for accelerating work and economic output, and alignment, which focuses on ensuring that increasingly capable systems behave safely and in accordance with human values. This paper articulates and develops a third, emerging ambition: the use of large language models (LLMs) as scientific instruments for studying human behavior, culture, and moral reasoning. Trained on unprecedented volumes of human-produced text, LLMs encode large-scale regularities in how people argue, justify, narrate, and negotiate norms across social domains. We argue that these models can be understood as condensates of human symbolic behavior, compressed, generative representations that render patterns of collective discourse computationally accessible. The paper situates this third ambition within long-standing traditions of computational social science, content analysis, survey research, and comparative-historical inquiry, while clarifying the epistemic limits of treating model output as evidence. We distinguish between base models and fine-tuned systems, showing how alignment interventions can systematically reshape or obscure the cultural regularities learned during pretraining, and we identify instruct-only and modular adaptation regimes as pragmatic compromises for behavioral research. We review emerging methodological approaches including prompt-based experiments, synthetic population sampling, comparative-historical modeling, and ablation studies and show how each maps onto familiar social-scientific designs while operating at unprecedented scale.

翻译：当代人工智能研究围绕两大主导抱负展开：一是生产力，即将AI系统视为加速工作和经济产出的工具；二是对齐，即聚焦于确保能力日益增强的系统安全运行并符合人类价值观。本文阐述并发展了一种新兴的第三种抱负：将大语言模型（LLMs）作为研究人类行为、文化与道德推理的科学工具。通过在海量人类生成文本上进行训练，LLMs编码了人类在不同社会领域中论证、辩护、叙述和协商规范的大规模规律性。我们认为这些模型可被理解为人类符号行为的凝聚态——一种经过压缩的生成式表征，使得集体话语模式能够通过计算方式被解析。本文将这一第三种抱负置于计算社会科学、内容分析、调查研究与比较历史研究等长期学术传统中，同时阐明了将模型输出视为证据的认知局限。我们区分了基础模型与微调系统，揭示了对齐干预如何系统性重塑或掩盖预训练阶段习得的文化规律，并指出指令微调与模块化适配机制可作为行为研究中的实用折衷方案。我们综述了包括提示实验、合成群体抽样、比较历史建模与消融研究在内的新兴方法论路径，阐明每种方法如何在实现前所未有的研究规模的同时，对应着社会科学中经典的研究设计范式。