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2026, no. 9
PHILOSOPHY & SOCIOLOGY

MANAGING SOCIOLOGICAL RISKS OF ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A CONTENT ANALYSIS OF INSTITUTIONAL POLICIES (RUSSIA, USA, CHINA, EUROPE)

Grigorii A. Chernichuk, Dmitry V. KataevORCID

DOI 10.20339/am.09-26.042pp. 42–49UDC 378-042:004(100)80 RUB

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Abstract

The integration of generative artificial intelligence (AI) into higher education creates new sociological risks: widening socioeconomic inequality, erosion of teacher professional autonomy, algorithmic bias, privacy threats, and the commercialization of educational activities. This article aims to identify and compare institutional policies governing the use of AI in universities. The empirical basis comprises the results of a content analysis of official documents and regulations from eight leading universities in Russia, the USA, China, and Europe, as well as regional universities in the Lipetsk region. The study identifies four governance models: decentralized (USA), centralized (China), ethical (Europe), and hybrid (leading Russian universities). A critical gap is revealed between metropolitan and regional Russian universities in the development of formal AI policies. While leading universities have detailed codes addressing academic integrity, transparency, and data protection, regional universities lack formal policies and focus primarily on technological infrastructure. The article substantiates the necessity of developing institutional policies for regional universities that include requirements for transparency, human oversight, and data protection.

Keywords

  • artificial intelligence in education
  • sociological risks
  • content analysis
  • institutional policies
  • risk management
  • higher education
  • digital divide
  • academic integrity

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PHILOSOPHY & SOCIOLOGY