超越外部视角：大语言模型时代社会科学的角色定位

郁建兴; 刘宇轩

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July 2026

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Citation: YU Jianxing and LIU Yuxuan. Beyond the Outside Observer: Repositioning the Social Sciences in the Era of Large Language Models[J]. Academic Monthly, 2026, 58(7): 77-89. shu

Beyond the Outside Observer: Repositioning the Social Sciences in the Era of Large Language Models

YU Jianxing ,
LIU Yuxuan

Abstract

As Large Language Models (LLMs) become deeply embedded in public governance, judicial assistance, and welfare allocation, social science is compelled to reexamine its own epistemological foundations. This article identifies three critical pitfalls in current social science research on LLMs:misinterpreting transient model deficiencies as structural social regularities, uncritically accepting manipulated benchmarks, and generalizing local optimizations of small-scale models into universal theories. To address these issues, the article establishes an epistemological boundary between engineering challenges and social propositions along two dimensions:whether a phenomenon can be resolved by scaling compute, and whether commercial logic provides sufficient incentive for its repair. This framework is crystallized into an operable four-quadrant matrix. Building on this foundation, the article identifies three research coordinates for social science:the linguistic erosion of administrative discretion, the selective disappearance of public values under optimization pressure, and the fracturing of accountability chains introduced by LLMs as a "fourth hand". The article further argues that the premise of social science standing "outside" AI is increasingly untenable.
- social science,
- LLM,
- AI,
- co-production
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1. [1]
  ZHANG Yi . Cognitive Transformation in Historical Research in the Age of AI——“Fluency-Induced Occlusion” in LLM-Assisted Reading of Diplomatic Manuscripts. Academic Monthly, 2026, 58(8): 29-40.
2. [2]
  WANG Qian . AI-Generated Content and Copyright Liability: Paradoxes and Resolutions. Academic Monthly, 2026, 58(8): 118-132.
3. [3]
  LIN Xifen , FU Zhangyi . How Does Public Trust in the Judiciary Shape Acceptability of Judges' AI-assisted Adjudications——An Empirical Study Based on Questionnaire Data. Academic Monthly, 2026, 58(8): 133-144.
4. [4]
  YOU Yang . How Does AI Understand Language Meaning. Academic Monthly, 2026, 58(8): 16-28.
5. [5]
  HE Da'an , LI Huaizheng . Digital Adjustment Mechanism in the Application of Artificial General Intelligence. Academic Monthly, 2026, 58(7): 54-63.
6. [6]
  WAN Yong , LI Yalan . Realizing the Function of Copyright Law in the Era of Artificial Intelligence. Academic Monthly, 2026, 58(7): 104-116.
7. [7]
  WEN Jun . From Technical Tokens to Social Tokens: the Ontological Construction of Token Sociology. Academic Monthly, 2026, 58(8): 145-156.
8. [8]
  XIE Yue . How State Capacity Is Generated in Practice——A Dynamic Equilibrium Model of Governance. Academic Monthly, 2026, 58(8): 106-117.
9. [9]
  XU Xiangdong . Consciousness and The Moral Status of AI Agents. Academic Monthly, 2026, 58(8): 5-15.
10. [10]
  ZHOU Mujun . Between Theory and Empirical Facts: Habermas and the Sociological Debate on the Public Sphere. Academic Monthly, 2026, 58(8): 157-170.

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

Beyond the Outside Observer: Repositioning the Social Sciences in the Era of Large Language Models

YU Jianxing
LIU Yuxuan

Abstract: As Large Language Models (LLMs) become deeply embedded in public governance, judicial assistance, and welfare allocation, social science is compelled to reexamine its own epistemological foundations. This article identifies three critical pitfalls in current social science research on LLMs:misinterpreting transient model deficiencies as structural social regularities, uncritically accepting manipulated benchmarks, and generalizing local optimizations of small-scale models into universal theories. To address these issues, the article establishes an epistemological boundary between engineering challenges and social propositions along two dimensions:whether a phenomenon can be resolved by scaling compute, and whether commercial logic provides sufficient incentive for its repair. This framework is crystallized into an operable four-quadrant matrix. Building on this foundation, the article identifies three research coordinates for social science:the linguistic erosion of administrative discretion, the selective disappearance of public values under optimization pressure, and the fracturing of accountability chains introduced by LLMs as a "fourth hand". The article further argues that the premise of social science standing "outside" AI is increasingly untenable.

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通讯作者: 陈斌, bchen63@163.com

Beyond the Outside Observer: Repositioning the Social Sciences in the Era of Large Language Models

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