RE-EXAMINING THE FUTURE PROSPECTS OF ARTIFICIAL INTELLIGENCE IN EDUCATION IN LIGHT OF THE GDPR AND ChatGPT
Abstract
Artificial intelligence in education (AIEd) is a fast-growing field of research. In previous work, we described efforts to explore the possible futures of AIEd by identifying key variables and their future prospects. This paper re-examines our discussions on the governance of data and the role of students and teachers by considering the implications of 1) a recent case related to the General Data Protection Regulation (GDPR) and 2) the release of ChatGPT, a generative AI model capable to producing ‘human-like’ text. These events raise questions for the future of AIEd and the underlying function of assessment, and highlight the importance of active student participation in the integration of AI in education.
Keywords
Artificial intelligence in education, General Data Protection Regulation, ChatGPT, writing and assessment, AI and society
Supporting Institution
Volkswagen Foundation and the Ministry of Science and Culture in Lower Saxony
Project Number
2N3743
Thanks
We thank the team of international researchers at the Center for Open Education Research (COER) for insightful discussions that shaped the elements in Table 1; particular thanks to Victoria I. Marín, Cengiz Hakan Aydin, Aras Bozkurt, Insung Jung, Junhong Xiao, and Patricia Slagter van Tryon for their active collaboration. We also thank Sreekari Vogeti and Laura N. Peters for their valuable comments on early drafts of this paper.
References
- AlgorithmWatch. (2020). Automating society report 2020. https://automatingsociety.algorithmwatch.org
- Bai, J. Y. H., Zawacki-Richter, O., Bozkurt, A., Lee, K., Fanguy, M., Cefa Sari, B., & Marin, V. I. (2022). Automated essay scoring (AES) systems: Opportunities and challenges for open and distance education. In Proceedings of The Tenth Pan-Commonwealth Forum on Open Learning (PCF10). https://doi.org/10.56059/pcf10.8339
- Bai, J. Y. H., Zawacki-Richter, O., & Müskens, W. (2022). Developing strategic scenarios for artificial intelligence applications in higher education. In 5th International Open and Distance Learning Conference Proceedings Book (pp. 47-70). Eskişehir, Turkey. https://iodl.anadolu.edu.tr/proceedings-iodl-2022
- Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big?. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610-623). https://doi.org/10.1145/3442188.3445922
- Bennett, R. (2005). Factors associated with student plagiarism in a post‐1992 university. Assessment & Evaluation in Higher Education, 30, 137-162. https://doi.org/10.1080/0260293042000264244Bincoletto, G. (2021). E-proctoring during students' exams: emergency remote teaching at stake. European Data Protection Law Review, 7, 586-591. https://doi.org/10.21552/edpl/2021/4/15
- Bommarito II, M., & Katz, D. M. (2022). GPT takes the Bar Exam. arXiv preprint. https://doi.org/10.48550/arXiv.2212.14402