OPPORTUNITIES AND RISKS IN UTILIZING AI IN EDUCATION FROM A DATA SCIENCE PERSPECTIVE

The article analyses the opportunities and risks of using artificial intelligence in educational systems from a data science perspective.The study's relevance is determined by the rapid development of intelligent technologies that contribute to the modernization of the educational process and the provision of personalized learning.It has been established that the integration of intelligent systems enables the automation of knowledge assessment, improves the quality of feedback, and predicts learners' academic performance.However, challenges remain in ensuring data privacy, algorithmic transparency, and minimizing algorithmic bias.The article's purpose is to analyze the effectiveness of artificial intelligence in education, identify key risks, and develop recommendations for implementing innovative systems to improve educational practices.Methodology.The study is based on a systematic analysis of educational data, comparing various intelligent system models, and assessing their impact on the learning process.Risk analysis methods were used to identify major threats and strategies for their mitigation.Scientific novelty.The article comprehensively analyses the applied aspects of using intelligent systems in education.Gaps in regulatory frameworks have been identified, and recommendations are provided for developing more transparent and adaptive algorithms that consider the needs of educational institutions and privacy requirements.Conclusions.Artificial intelligence can enhance the efficiency of educational processes, provided ethical standards are upheld and mechanisms for algorithmic transparency are implemented.Recommendations for the safe use of intelligent systems include data anonymization, algorithm audits, and increasing the digital competence of education process participants.