Taming Frankenstein’s monster: Ethical considerations relating to generative artificial intelligence in education

ABSTRACT

The emergence of generative artificial intelligence (GAI) in the past two years is exerting profound effects throughout society. However, while this new technology undoubtedly promises substantial benefits, its disruptive nature also means that it poses a variety of challenges. The field of education is no exception. This position paper intends to deepen our current understanding of GAI in education from the perspective of ethics. We begin by discussing the definition and unique features of GAI, highlighting its advanced cognitive abilities and how they present challenges to academic ethics. The paper then reviews examples of existing university regulations related to the use of GAI in teaching and learning, and identifies areas in need of further attention. Using a tripartite model that comprises the different stakeholders of students, educators and school administrators, the paper outlines the pertinent principles that promote responsible and ethical GAI utilization in the field of education.

KEYWORDS:

• Generative artificial intelligence
• ethics
• regulations
• model
• principles

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Some recent studies (e.g., Coda-Forno et al., 2023; Lewis & Sarkadi, 2023) have suggested GAI may possess or at least can reflect emotions, and it is also capable of reflexivity. For example, a recent study by (Coda-Forno et al. (2023) showed that GPT-3.5 became more biased when prompted with anxiety-inducing text, affecting its performance in tasks.

2. GAI is able to assist students in multiple and creative ways. Students, for example, can use GAI as a learning advisor, a language tutor, and a brainstorming partner, etc. In this paper, we only focus on using GAI to write material for academic purposes, as it is the use that has raised most ethical concerns in the field of education.

3. By the time of publication, HKU has reversed their attitudes by removing the six-month ban on using GAI and providing free access to all teachers and students for teaching and learning purposes. Please see more from https://hku.hk/press/news_detail_26434.html

Additional information

Funding

The work was supported by the Humanities and Social Science Fund of Ministry of Education of China [23YJC880131].

Notes on contributors

Zi Yang

Zi Yang is an Assistant Professor at the Institute of Education, Xiamen University. Her research interests include educational technology, higher education, and classroom pedagogy.

Junjie Gavin Wu

Junjie Gavin Wu is a Tenured Lecturer (equivalent to Assistant Professor) and a Ph.D. Supervisor in the Faculty of Applied Sciences, Macao Polytechnic University. He is a Shenzhen High-Caliber Talent and Vice President of PacCALL. Gavin sits on the organizing committee of various international associations such as iLRN, GLoCALL and ChinaCALL. He serves on the editorial board of several leading journals such as IEEE Transactions on Learning Technologies, Computers and Education: Artificial Intelligence, TESL-EJ, and Computers & Education: X Reality. Gavin has authored around 40 English publications, with over 15 papers appeared in SSCI journals. He also edited books with Routledge and Springer and spearheaded 7 special issues such as Educational Technology & Society.

Haoran Xie

Haoran Xie is the Head and Associate Professor of the Department of Computing and Decision Sciences at Lingnan University, Hong Kong. His research interests include artificial intelligence in education, machine learning, and big data. He has more than 390 publications. He is the Editor-in-Chief of Computers & Education: Artificial Intelligence, Natural Language Processing Journal, and Computers & Education: X Reality, and Co-Editor-in-Chief of Knowledge Management and E-Learning. He has been listed as the World’s Top 2% scientist by Stanford University.