Assessing the Pros and Cons of AI-Supported Learning in Education (Position Paper)

Abstract

This study aims to analyze the applications of artificial intelligence (AI) in education, starting from the challenges related to improving teaching and learning processes alongside the significant transformative potential offered by this field. The study adopted a literature review methodology, with data collected from peer-reviewed academic journals, books, and research reports, which were then systematically classified into key themes, including the role of AI in enhancing learning experiences, educational management, and ethical considerations. The findings indicate that there are two prominent types of AI: “classical AI,” which focuses on data processing and decision-making, and “generative AI,” which creates original content. This distinction is essential for understanding how these technologies can be effectively employed in educational contexts. The study concludes that AI provides tangible benefits, such as improving the efficiency of educational systems, enhancing data management, and offering personalized learning. However, it also raises major challenges related to privacy, security, fairness, and the risk of job displacement. Therefore, the study emphasizes the need for a balanced approach that integrates technological advancement with ethical and practical considerations to ensure the effective and sustainable use of AI in education. The originality of this study lies in presenting a comprehensive and systematic analysis that balances the technical potential of AI with its ethical and social challenges in the educational sector. Rather than merely reviewing benefits and drawbacks, it offers a critical and balanced perspective grounded in recent literature, thereby opening new avenues for scholarly debate on how to integrate AI effectively into education while preserving values of equity, fairness, and the quality of the learning process.