ChatGPT in Education: Ethical Predicaments of Generative AI
DOI:
https://doi.org/10.62051/bejkn640Keywords:
Education; Generative AI; ChatGPT; Educational Ethics.Abstract
ChatGPT, which stands for generative artificial intelligence technology, has become the current prominent topic in the realm of education. The innovative practice of artificial intelligence technology in the field of education has laid a technical foundation for ChatGPT to empower college education, and ChatGPT has also been deeply applied in the fields of educational resource recommendation, language learning support, and personalized learning assistance due to its strong text understanding. It brings vast opportunities for the development of high-quality education, whilst also generating ethical risks for its use. Based on the perspective of educational ethics, this study finds that the ethical problems of generative AI education are mainly reflected in the weakening of the stability of the teacher-student relationship, the impact of privacy protection, and academic misconduct caused by improper human-computer interaction. Accordingly, this paper proposes a series of strategies to alleviate educational ethics from multiple perspectives, such as reconstructing the institutional ethics of data governance, improving the policy system, and strengthening the dominant position of students, so as to guide teachers and students in colleges and universities to maintain rational thinking, prudently use new technologies such as ChatGPT, and promote the development of intelligent education in the new era in the direction of standardized and orderly, human-machine coexistence.
Downloads
References
Li, T. (2002). Artificial Intelligence. Chongqing: Chongqing University Press.
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI Chatbots in Education: Systematic Literature Review. International Journal of Educational Technology in Higher Education, 20.
Gao, H., et al. (2012). Political Ethics: The Perspective of Historical Materialism. Harbin: Heilongjiang People’s Publishing House.
Tian, F. (2021). “Data Worship” to “Data Justice”: The Transformation of Higher Education Research Paradigm in the Era of Artificial Intelligence. Tsinghua University Education Research, 1: 77-85.
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI Chatbots in Education: Systematic Literature Review. International Journal of Educational Technology in Higher Education, 20.
Wu, H. & Du, Y. (2021). Ethical Governance of Artificial Intelligence: From Principles to Action. Studies in Dialectics of Nature, 4: 49-54.
Song, X., Liu, M., & Chen, J. (2023). A Comprehensive Analysis of the Impact of GPT-4: High-quality Economic Development and National Security Prevention. Journal of Guangdong University of Finance and Economics, 38(2): 100-112.
Wang, Y., Wang, D., Liang, W., & Liu, C. (2023). “Aladdin’s Magic Lamp” or “Pandora’s Box”: The Potential and Risks of ChatGPT’s Educational Applications. Modern Distance Education Research, 35(2): 48-56.
Zhu, S. (2023). The Transformation of the Role of Vocational Education Teachers in the Era of Artificial Intelligence. Education Horizons, 40: 55-59.
Zhang, Y., Qin, Z., & Xiao, L. (2017). The Discriminatory Nature of Big Data Algorithms. Studies in Dialectics of Nature, 33(5): 81-86.
Abid, A., Farooqi, M., & Zou, J. (2021). Persistent Anti-Muslim Bias in Large Language Models. Arxiv.org. https://arxiv.org/abs/2101.05783
Weidinger, L., et al. (2022). Taxonomy of Risks Posed by Language Models. 2022 ACM Conference on Fairness, Accountability, and Transparency.
Yu, X. & Li, L. (2020). Design Ethics of Artificial Intelligence. Science and Society, 10(2): 75-88.
Tian, X. (2020). Privacy Protection and Open Sharing: Reform of Educational Data Governance in the Era of Artificial Intelligence. Electronic Education Research, 41(5): 33-38.
Miao, G. (2023). Integrity and Innovation: Research on the Reconstruction of Teacher-Student Relationship under the Impact of ChatGPT. Education Horizons, 17: 15-18.
Ma, C. (2004). The New Requirements of Juche Education for Students’ Learning and Teacher-Student Relationship. Journal of Jiangsu Institute of Education (Social Sciences), 6:19-20.
Zhang, S., Yang, M., & Liu, S. (2023). The Content and Steps of Heuristic Case Teaching Based on Constructivist Learning Theory- an Example of Teaching Leadership Science. New Curriculum Teaching (Electronic Edition), 21: 84-86.
Qiu, Z. & Li, X. (2024). Five Challenges of ChatGPT to Ideological and Political Education in Colleges and Universities. Chinese Journal of Medical Education Technology, 38(01): 58-69.
Zhou, M. & Bin, G. (2024). Bias and Regulation in the Communication of Generative Artificial Intelligence: A Case Study of ChatGPT. Learning and Practice.
Downloads
Published
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
