Rethinking education: artificial Intelligence, empathy, and emerging ethical challenges

SOFIA KOTSINI SOFIA KOTSINI

Abstract

This paper examines how artificial intelligence (AI) enters classrooms and changes the way teachers and students relate to each other. We focus on both the opportunities it offers and the ethical questions it raises. Using the framework of Emotional-Intelligence (EI) theory, we reviewed sixty-eight studies published between 2016 and 2025. The review draws together findings on personalised learning systems, predictive analytics, affect-sensing tools, and the automation of routine schoolwork. When these technologies are carefully regulated, they can help teachers and learners develop self-awareness, social understanding, and stronger classroom relationships. At the same time, concerns about bias in algorithms, constant data collection, the loss of personal contact, and gaps in teacher training still threaten fair and empathic use of AI. We suggest policies, teacher-training measures, and design practices that keep human connection at the centre of learning so that AI supports, rather than replaces, the empathy that education depends on.

Keywords

Artificial intelligence; empathy; ethical challenges; human-centered education; socio-emotional learning

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References

AlZu’bi, S., Alsmirat, M., & Alsmadi, I. (2022). Deep learning methods for emotion detection in educational settings. Frontiers in Psychology, 13, 1387089.

Bennett, L. (2024). Artificial intelligence and its potential impact on the higher education sector. Athens Journal of Education, 11(3), 2-14.

Cios, K. J., & Zapala, D. (2023). Artificial intelligence and bias in education: A review. Computers & Education: Artificial Intelligence, 4, 100123.

Cohen, D., & Strayer, J. (2016). Empathy in education: Engagement, values, and achievement. Educational Psychologist, 51(2), 131-147.

Derakhshan, A., Matsuda, S., & Zhang, J. (2025). Investigating the usefulness of AI-driven robots in establishing empathy and communication. Computers in Human Behavior, 147, 107923.

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., … & Schafer, B. (2018). AI4People - An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689-707.

García, M., Zhang, Y., & Jones, A. (2022). AI-driven virtual reality for empathy development in education. International Journal of Academic Research in Business and Social Sciences, 15(3), 711-725.

Goleman, D. (1995). Emotional intelligence: Why it can matter more than IQ. Bantam Books.

Greenhalgh, T., Thorne, S., & Malterud, K. (2018). Time to challenge the spurious hierarchy of systematic over narrative reviews? European Journal of Clinical Investigation, 48(6), e12931.

Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning (2nd ed.). Center for Curriculum Redesign.

Immordino-Yang, M. H., & Damasio, A. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3-10.

Jamaluddin, N. S., & Mokhtar, M. (2025). Teaching empathy: How AI can support the development of soft skills in education. International Journal of Academic Research in Business and Social Sciences, 15(3), 704-721.

Jennings, P. A., & Greenberg, M. T. (2009). The prosocial classroom: Teacher social and emotional competence in relation to student and classroom outcomes. Review of Educational Research, 79(1), 491-525.

Liu, Y., & Li, C. (2024). Artificial intelligence and adaptive learning: Opportunities and challenges. Journal of Educational Technology Research, 41(2), 213-230.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.

Martin, A. (2025). Classrooms are adapting to the use of artificial intelligence. Monitor on Psychology, 56(1), 24-27.

Shah, H. (2022). Artificial empathy: The promise and pitfalls of AI in education. AI & Society, 37, 233-245.

Tapp Jaksa, A., & Margerum-Leys, J. (2024). Enhancing cognition through affect within AI-driven technology. In 17th annual International Conference of Education, Research and Innovation 2024 Proceedings (pp. 8250-8254). IATED

U.S. Department of Education, Office of Educational Technology. (2024). AI and the future of teaching and learning: Insights and recommendations. Washington, DC.

UNESCO. (2025). Recommendation on the ethics of artificial intelligence. https://www.unesco.org.

Vieriu, A. M. (2025). The impact of artificial intelligence on students’ learning processes and academic performance. Education Sciences, 15(3), 343.

Vistorte, A. O., Ribeiro, W., Jaen, J., Kahn, K., & Backes, B. (2024). Predictive analytics in education: Benefits, risks, and ethical challenges. Journal of Learning Analytics, 11(2), 87-104.

Williams, T. (2024). Ethical and regulatory challenges of generative AI in education. Frontiers in Education, 9, 1565938.

Williamson, B., & Piattoeva, N. (2022). Education governance and datafication: Artificial intelligence, algorithms, and automation. Educational Philosophy and Theory, 54(3), 221-236.

World Economic Forum. (2025). Using AI in education to help teachers and their students. https://www.weforum.org.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial-intelligence applications in higher education. Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27.


DOI: https://doi.org/10.26220/mje.5533

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Mediterranean Journal of Education | ISSN: 2732-6489 |  Department of Educational Sciences and Early Childhood Education - University of Patras.

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