Potential and risks of using artificial intelligence in education

Abstract

The article analyzes the potential and risks of using artificial intelligence in education in the context of the transformation of the modern educational environment. It examines the evolution of approaches to defining artificial intelligence – from classical notions of “intelligent machines” to a contemporary understanding of AI as a complex sociotechnical system that combines autonomy, adaptability, and learning capability. A review of scientific research is carried out, revealing the theoretical foundations of implementing artificial intelligence in education, including the concepts of intelligent infrastructure, constructionism, and the synergy between human and machine intelligence. The key areas of artificial intelligence application in the educational process have been identified, including the personalization of learning, the creation of adaptive learning environments, the automation of assessment, the development of educational analytics, and the support of teachers’ professional activities. It is shown that artificial intelligence contributes to improving learning efficiency, enables individual learning trajectories, and expands teachers’ pedagogical capabilities. At the same time, it is substantiated that the integration of artificial intelligence is accompanied by a number of risks, with particular attention given to issues of personal data protection, algorithmic bias, the reduction of the teacher’s role, dependence on technology, and a potential decline in learners’ critical thinking skills. Social and ethical challenges are also considered, including unequal access to technologies and questions of responsibility for decisions made by AI systems. It is concluded that artificial intelligence in education is a complex phenomenon capable of transforming all key components of the educational process. The potential of artificial intelligence lies in improving learning efficiency through the adaptation of educational content, the individualization of learning pathways, the automation of assessment, the expansion of teachers’ capabilities, and the development of new digital and AI competencies among learners. Artificial intelligence is becoming a driving force in the transition toward a more flexible and personalized educational model.