Russia Sets Clear Rules for Integrating AI into Education
In Russia, researchers have developed a step‑by‑step framework to help universities safely integrate large language models into the learning process while minimizing risks and preserving educational quality.
A Structured Approach to AI in Academia
Researchers at the Higher School of Economics (HSE University) have introduced a clear and gradual scheme that universities can use to integrate large language models into the educational process. The framework is based on an analysis of real failures and mistakes encountered by students and professors when working with AI systems. Its primary goal is to create transparent rules, reduce risks, and support the responsible use of modern technologies without compromising academic standards.
According to the authors, large language models have significantly transformed academic life over the past two years. Students and instructors increasingly rely on AI, but verifying originality and accuracy has become more challenging. Researchers from the St. Petersburg School of Economics and Management analyzed situations where neural networks generated incorrect answers, relied on dubious data, or became difficult to control due to unclear usage rules. Based on these findings, they developed a step‑by‑step scheme that helps identify vulnerabilities before institutions scale AI technologies across the university.
Step‑by‑Step Safety
The methodology includes several consecutive stages: auditing current AI tools, assessing risks related to data quality and confidentiality, testing solutions in controlled “sandbox” environments, and only after that — expanding them to the entire university with regular monitoring. As associate professor and co‑author Andrey Ternikov explained, the framework “translates the conversation about AI from general words into a clear plan” with defined roles, priorities, and control points.
Testing showed that many risks can be mitigated through data anonymization, strong security protocols, user training, and flexible technical solutions. The authors emphasize that adopting this methodology helps educational institutions cultivate a culture of responsible AI use. In practice, this means universities can fully harness the advantages of AI without diminishing educational standards.
