TEACHERS’ ETHICAL CONCERNS AND PERCEPTIONS OF PROFESSIONAL RESPONSIBILITY IN THE AGE OF ARTIFICIAL INTELLIGENCE
Keywords:
AI Ethics, teacher responsibility, data privacy, algorithmic justice, professional autonomyAbstract
The aim of this study is to examine the ethical concerns and professional responsibility perceptions of teachers regarding the integration of artificial intelligence technologies into educational settings with a holistic approach. In today's world where digital transformation in education is accelerating, it is aimed to understand not only the technical competencies of teachers but also their experiences in the context of data privacy, algorithmic justice, and professional autonomy. The research was designed according to the qualitative research method and the phenomenology design was adopted. The study group consists of 10 teachers working in different branches, determined using criterion sampling, one of the purposeful sampling methods. The data were collected through a semi-structured interview form developed by the researcher and analyzed using the content analysis technique. According to the research findings, teachers view artificial intelligence tools as a powerful assistant that saves time rather than a factor threatening the profession. However, despite this optimistic approach, it has been determined that the teachers' biggest concern is student data privacy and surveillance (digital panopticon). In addition, participants have a strong awareness that artificial intelligence algorithms may harbor historical and societal biases, and this situation may damage equal opportunity in education and lead to justice problems. The lack of transparency in the decision-making processes of current artificial intelligence systems (the black box problem) makes it difficult for teachers to trust the system and ensures accountability.
As a result of the study, it was observed that the teaching profession has evolved from being a transmitter of knowledge to a role of ethical gatekeeper and digital mentorship that designs the learning process and supervises artificial intelligence outputs. Teachers argue that the final decision and responsibility should remain under human supervision; however, they state that current in-service trainings are insufficient in covering ethical and pedagogical dimensions.
References
Akgun, S. ve Greenhow, C. (2021). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2, 431–440.
https://doi.org/10.1007/s43681-021-00049-4
Aydın, İ. (2016). Eğitim ve öğretim etiği. Pegem Akademi.
Baker, R. S. ve Hawn, A. (2021). Algorithmic bias in education. International Journal of Artificial Intelligence in Education, 32, 1052–1092.
https://doi.org/10.1007/s40593-021-00268-5
Banks, J. A. (2009). The Routledge international companion to multicultural education. Routledge.
Biesta, G. (2015). The beautiful risk of education. Paradigm Publishers.
Biesta, G. (2017). The rediscovery of teaching. Routledge.
Bozkurt, A. (2023). ChatGPT, üretken yapay zekâ ve algoritmik paradigma değişikliği. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 9(1), 7–17.
Campbell, E. (2003). The ethical teacher. Open University Press.
Coe, R. (2020). The role of evidence in teaching and learning. İçinde The guide to evidence-based teaching. Catapult.
Dignum, V. (2019). Responsible artificial intelligence: How to develop and use AI in a responsible way. Springer. https://doi.org/10.1007/978-3-030-30371-6
European Commission. (2019). Ethics guidelines for trustworthy AI. High-Level Expert Group on Artificial Intelligence.
Fischman, G. E., DiBello, L. ve Gardner, H. (2006). The challenges and potential of Internet-based interactions for social responsibility. The Journal of Aesthetic Education, 40(2), 39–51.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V. ve Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Ho, A. D. ve diğerleri (2017). Big data analysis for MOOCs. University of Pennsylvania Press.
Holmes, W., Bialik, M. ve Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Holstein, K., McLaren, B. M. ve Aleven, V. (2019). Co-designing a real-time classroom orchestration tool to support teacher–AI complementarity. Journal of Learning Analytics, 6(2), 27–52. https://doi.org/10.18608/jla.2019.62.3
Jobin, A., Ienca, M. ve Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399.
https://doi.org/10.1038/s42256-019-0088-2
Jonas, H. (1984). The imperative of responsibility: In search of an ethics for the technological age. University of Chicago Press.
Kizilcec, R. F., Pérez-Sanagustín, M., Maldonado, J. J., & Morales, N. (2017). Closing the loop: Teacher and student trust in an adaptive educational technology. İçinde Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. https://doi.org/10.1145/3051457.3051463
Knox, J. (2020). Artificial intelligence and the end of the human: The “post-humanist” displacement of the teacher. Postdigital Science and Education, 2(3), 674–688.
https://doi.org/10.1007/s42438-020-00120-3
Lauermann, F. ve Karabenick, S. A. (2013). The meaning and measure of teachers’ sense of responsibility for educational outcomes. Teaching and Teacher Education, 30, 13–26. https://doi.org/10.1016/j.tate.2012.10.001
Long, D. ve Magerko, B. (2020). What is AI literacy? Competencies and design considerations. İçinde Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems.
https://doi.org/10.1145/3313831.3376727
Lupton, D. ve Williamson, B. (2017). The datafied child: The dataveillance of children and implications for their rights. New Media ve Society, 19(5), 780–794.
https://doi.org/10.1177/1461444816686328
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K. ve Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys (CSUR), 54(6), 1–35. https://doi.org/10.1145/3457607
Milli Eğitim Bakanlığı. (2015). Öğretmenlik mesleği genel yeterlikleri. Öğretmen Yetiştirme ve Geliştirme Genel Müdürlüğü.
Müller, V. C. (2020). Ethics of artificial intelligence and robotics. Stanford Encyclopedia of Philosophy.
OECD. (2020). Back to the future of education: Four OECD scenarios for schooling. OECD Publishing. https://doi.org/10.1787/178ef527-en
Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
Reich, J. (2020). Failure to disrupt: Why technology alone can’t transform education. Harvard University Press.
Santoro, D. A. (2011). Good teaching in difficult times: Demoralization in the pursuit of good work. American Journal of Education, 118(1), 1–23.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Slade, S. ve Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529.
https://doi.org/10.1177/0002764213479366
Solbrekke, T. D. ve Englund, T. (2011). Bringing professional responsibility back in. Studies in Higher Education, 36(8), 847–861.
https://doi.org/10.1080/03075079.2010.482205
UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO Publishing.
Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.
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