TEACHING AND LEARNING IN AN AGE OF ARTIFICIAL INTELLIGENCE: REVISITING MARTIN BUBER'S PHILOSOPHY OF DIALOGUE AND ITS IMPLICATIONS FOR HUMAN-CENTERED EDUCATION IN AN ERA OF INTELLIGENT MACHINES
DOI:
https://doi.org/10.65336/WJAEL.2026.3901Keywords:
Artificial Intelligence, Martin Buber, Philosophy of Education, Dialogue, “I–Thou”, “I–It”, Educational Technology, Human Formation.Abstract
The growing integration of artificial intelligence (AI) systems and tools in educational practice has generated extensive scholarly interest, with existing literature focusing predominantly on the capacity of these systems to personalize learning and expand access to educational resources. These developments have substantially advanced the understanding of AI's pedagogical potential. However, they also propagate a reductive framework in which AI’s use in educational practice is evaluated primarily on the basis of scalability and performance. Little attention has been given to the philosophical considerations about personhood and the nature of educational relationships that shape its integration into teaching and learning. Addressing this gap, this article examines the educational implications of artificial intelligence through Martin Buber's philosophy of dialogue, with particular reference to the “I–Thou” and “I–It” modes of relation. The paper adopts a philosophical-analytic methodology to examine whether the operational dynamics of AI are compatible with Martin Buber's idea of authentic education. The article argues that the operational logic of AI is situated within the “I–It” mode of relation, insofar as its pedagogical functions depend on objectifying learners through computational models. From a Buberian perspective, this objectification is not in itself philosophically problematic or educationally illegitimate. The dynamic of objectification becomes philosophically problematic only when it expands beyond its appropriate epistemic domain and begins to structure educational relationships through categories of measurement and control. To this effect, the article argues that authentic education presupposes a pedagogical encounter characterized by mutual presence and the irreducibility of the human ‘subject’, which are all conditions that AI, irrespective of its computational sophistication, cannot instantiate. At least, not at the current stage of its development. The article concludes that AI is a powerful resource whose educational value ultimately lies in its capacity to support, rather than supplant the dialogical relationship between teachers and learners.
References
1. Aristotle. (2009). Nicomachean ethics (W. D. Ross, Trans.; L. Brown, Ed.). Oxford University Press. (Original work composed ca. fourth century BCE)
2. Biesta, G. J. J. (2020). Educational research: An unorthodox introduction. Bloomsbury Academic.
3. Biesta, G. J. J. (2020). Risking ourselves in education: Qualification, socialization, and subjectification revisited. Educational Theory, 70(1), 89–104. https://doi.org/10.1111/edth.12411
4. Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16. https://doi.org/10.3102/0013189X013006004
5. Bruner, J. S. (1966). Toward a theory of instruction. Harvard University Press.
6. Buber, M. (1947). Between man and man (R. G. Smith, Trans.). Routledge & Kegan Paul.
7. Buber, M. (1970). I and Thou (W. Kaufmann, Trans.). Charles Scribner's Sons. (Original work published 1923)
8. Dewey, J. (1916). Democracy and education: An introduction to the philosophy of education. Macmillan.
9. Freire, P. (1970). Pedagogy of the oppressed. Continuum.
10. Friedman, M. (1983). Martin Buber: The life of dialogue (4th ed.). University of Chicago Press.
11. Harari, Y. N. (2024). Nexus: A brief history of information networks from the Stone Age to AI. Random House.
12. Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning (2nd ed.). Center for Curriculum Redesign.
13. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeiffer, F., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
14. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
15. Molnar, A. R. (1997). Computers in education: A brief history. T.H.E. Journal, 24(11), 63–68.
16. Noddings, N. (1984). Caring: A feminine approach to ethics and moral education. University of California Press.
17. Piaget, J. (1952). The origins of intelligence in children (M. Cook, Trans.). International Universities Press. (Original work published 1936)
18. Rousseau, J.-J. (1979). Emile, or On education (A. Bloom, Trans.). Basic Books. (Original work published 1762)
19. Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
20. Selwyn, N. (2016). Education and technology: Key issues and debates (2nd ed.). Bloomsbury Academic.
21. Taylor, C. (1989). Sources of the Self: The Making of the Modern Identity. Harvard University Press.
22. Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners (2nd ed.). ASCD.
23. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000381137
