Ethics in the Use of Artificial Intelligence in Education: A Systematic Review (#2281)

Authors

Pacco Huamani, Gabriela Mistral

Abstract

This systematic review examines the ethical implications of artificial intelligence (AI) implementation in educational environments. Through a comprehensive analysis of peer-reviewed literature published between 2021 and 2026, this study identifies key ethical concerns, including privacy and data protection, algorithmic bias and fairness, transparency and explainability, student autonomy, and the digital divide. The review synthesizes findings from 41 selected studies using PRISMA methodology, revealing that while AI offers significant potential to personalize learning and improve educational outcomes, it also raises critical ethical challenges that require careful consideration. Major concerns include the collection and use of student data, potential discrimination through biased algorithms, lack of transparency in AI decision-making processes, and unequal access to AI-enhanced educational resources. The study proposes a comprehensive ethical framework for AI implementation in education based on principles of beneficence, non-maleficence, autonomy, justice, and explicability. Recommendations are provided for educators, policymakers, and technology developers to ensure responsible and equitable AI integration in educational settings.