AI Ethics in the Fields of Education and Research: A Systematic Literature Review

The rapid emergence of artificial intelligence tools and their integration into various societal sectors have introduced significant ethical challenges. This research focuses on identifying the most frequently discussed ethical aspects of AI within the realms of education and research. A systematic literature review, supported by AI-driven tools, was conducted to address this objective. The study reveals that key ethical aspects recurrently examined include transparency and explainability, privacy and data protection, responsibility and accountability, and equity. Transparency and explainability are crucial for ensuring that AI systems in education operate in a comprehensible manner, fostering trust among educators and students. Privacy and data protection emphasize the importance of handling personal data with utmost care, adhering to relevant regulations. Responsibility and accountability highlight the need for clear mechanisms for overseeing AI deployment, while equity addresses the avoidance of bias and discrimination. The findings underscore the necessity of addressing a broad spectrum of ethical considerations throughout the lifecycle of AI systems to promote their responsible use in educational and research settings.