Ethical artificial intelligence for teaching-learning in higher education

This paper proposes a human-centered approach to using Artificial Intelligence (AI) in higher education that promotes equitable access to knowledge while preserving privacy and ethics. Through the lens of third-generation Activity Theory we examine the interaction between three activity systems in higher education: AI teachers, human teachers, and students. Our multi-role design recognizes the role of different actors and AI-based tools and technologies, highlighting the importance of understanding how these different systems interact and influence one another in order to effectively design and implement ethical educational technology solutions. By constructing an interaction space between these systems, we gained a deeper understanding of the dynamics of teaching-learning in higher education. Based on this analysis, we frame and design our Ethical AI in Education (EAIED) multi-platform, integrating recent development in AI in education systems, pedagogical strategies, and complying with ethical guidelines recommendation. The EAIED emphasizes data privacy, ethics, and interoperability between learning systems. This approach offers interactive, personalized, and equitable teaching-learning experiences that lead to developing critical thinking, higher-order skills, improving engagement, communication, and expansive learning.