Education
The rapid development of generative artificial intelligence (AI), combined with natural language processing, computer vision, and speech recognition technologies, is making human–machine interaction increasingly intuitive and effective. The latest AI-powered digital assistants—text chatbots, voice assistants, and autonomous AI agents—do more than simply answer questions and execute commands according to predefined rules. They can engage in dialogue, adapt to context, and solve fairly complex intellectual tasks, explaining their solutions through so-called ‘Chains of Thought’ (CoT).
As a result, the role of digital services and systems is undergoing a transformation. Essentially, they are no longer mere automation tools; they are evolving into full-fledged assistants with whom humans can think, discuss ideas, and make decisions collaboratively. This is driving innovation in almost every area of our lives: manufacturing, finance, healthcare, communications, art and, of course, education.
New opportunities for educational platforms
Key areas of AI application in education[1]include the following:
Building personalized learning trajectories based on the student's digital footprint
Automating knowledge assessment
Intelligent educational simulators (AI tutors and mentors available 24/7)
Automatic generation of educational content, tests, assignments, and curriculums
Recommendation systems for selecting learning materials
Virtual labs with VR/AR technologies for experiential learning
Tools to prevent plagiarism and cheating during remote exams
Enhancing accessibility in education
Thus, the scope of AI applications in education is exceptionally broad. Some examples include:
- automatic adaptation of learning materials, assignments, and teaching style to each student;
- automatic grading of assignments, feedback and error analysis;
- automatic summarizing of large volumes of text, video, or audio content;
- checking student work for originality and plagiarism;
- biometric identification of students during remote exams;
- monitoring students to detect cheating patterns;
- real-time translation of text and speech into multiple languages in real time and adaptation for people with disabilities.
Risks of AI in education
Even this limited list of tasks shows that AI in education must meet the strictest safety requirements. After all, it handles students' personal information—including behavioral profiles—and directly influences the learning process through assessment and recommendation systems.
At the same time, the risks of using AI in education go beyond technical vulnerabilities such as data leaks or system manipulation. You can read more about these vulnerabilities in the relevant section of our website. Ethical challenges are equally significant, for example:
- the spread of plagiarism and increasingly sophisticated ways of deceiving teachers using generative AI;
- receiving unreliable information from AI or reinforcement of stereotypes due to incomplete or biased training data;
- issues of transparency, fairness, and non-discrimination in automated grading;
- overreliance on AI, leading to a blurring of the teacher's role as well as a decline in students' critical thinking and independent learning skills.
Standards
To ensure AI in education is not only effective, but also as safe and ethical as possible[2], relevant standards are being actively developed and implemented.
As of March 2025, Russia has approved 14 standards[3] in the field of AI for education in the following areas:
Optimization of learning processes
(see, for example, [4-6])
Educational products with AI algorithms for adaptive learning [9]
Thus, AI offers clear benefits for education—personalizing learning for students and automating routine tasks for teachers. However, its full integration demands a responsible, carefully considered approach. Innovation must go hand in hand with rigorous quality control and data protection, transparent and secure algorithms and attention to its social impact.
Sources
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- 1. GOST R 59895-2021 «Artificial intelligence technologies in education. General provisions and terminology».
- 2. PNST 840-2023 (ISO/IEC TR 24368:2022) «Artificial intelligence. Overview of ethical and societal concerns».
- 3. https://tc164.ru/page58072225.html
- 4. GOST R 70951-2023 «Artificial intelligence technologies in education. Functional subsystem for managing the progress of students in additional professional education programs. General provisions and test procedure».
- 5. GOST R 70947-2023 «Artificial intelligence technologies in education. Functional subsystem for managing the progress of students in secondary vocational education programs. General provisions and test procedure».
- 6. GOST R 70950-2023 «Artificial intelligence technologies in education. Functional subsystem for managing the progress of students in the programs of training scientific and scientific-pedagogical personnel in postgraduate studies. General provisions and test procedure».
- 7. GOST R 59897-2021 «Data for artificial intelligence systems in education. Requirements for the collection, storage, processing, transmission and protection of data».
- 8. GOST R 59900-2021 «Artificial intelligence systems. Typical requirements for check samples of initial data for testing artificial intelligence systems in education».
- 9. GOST R 59899-2021 «Educational products with algorithms of artificial intelligence for adaptive learning in general education. Technical requirements».
- 10. GOST R 70949-2023 «Artificial intelligence technologies in education. The application of artificial intelligence in research activities. Use cases».
- 11. GOST R 71657-2024 «Artificial intelligence technologies in education. Functional subsystem for creating scientific publications. General provisions».