Alex MITCHELL1*, Weiyu ZHANG1, Jingyi XIE1, Bimlesh WADHWA2, and Eric KERR3
1Department of Communications and New Media, Faculty of Arts and Social Sciences
2Department of Computer Science, School of Computing
3Tembusu College and Asia Research Institute (ARI)
Mitchell, A., Zhang, W., Xie, J., Wadhwa, B., & Kerr, E. (2023). Exploring activity-based instructional approaches to develop students’ understanding of the ethical implications of technology [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/exploring-activity-based-instructional-approaches-to-develop-students-understanding-of-the-ethical-implications-of-ict/
SUB-THEME
AI and Education
KEYWORDS
IT ethics education, technology design, educational strategies, activity-based instruction
CATEGORY
Paper Presentation
ABSTRACT
Information and communications technology (ICT) such as artificial intelligence (AI) offers tremendous opportunities to benefit society, but raises concerns over potential harm to social good. While ICT education has focused on advancing technologies, there is less emphasis on embedding ethical considerations in the learning of ICT. There is increasing public concern over the unethical consequences of ICT development and usage, particularly given the recent widespread adoption of AI-based tools such as ChatGPT. This suggests a need for the educational community “to renew its emphasis on nurturing the ability to recognize and engage with ethical issues emerging in relation to AI” (Borenstein & Howard, 2021) and ICT more generally. This paper presentation describes our exploration of activity-based instructional approaches to help students gain a better understanding of the ethical implications of ICT.
Current approaches to ICT ethics education can be categorised into three groups: ethical guidelines, fairness toolkits, and activity-based approaches (Zhang, 2022). Using ethical guidelines as a starting point for ICT ethics education can be problematic, as current guidelines tend to take an action-restricting, checkbox-based approach, making them inherently limiting and hard to adapt to specific situations (Hagendorff, 2020). In addition, students often find ethics education dry and hard to apply when education emphasises philosophical principles without accounting for real-life complexities. Similarly, fairness toolkits have limitations in terms of adaptability, and, if poorly designed, “could engender false confidence in flawed algorithms” (Lee & Singh, 2021). Activity-based co-design approaches, such as design fiction and speculative design (Baumer et al., 2020; Pierce, 2021), offer an alternative to more traditional approaches, and address the call for AI ethics education to move beyond approaches grounded in instructionism (Holmes et al., 2022).
This paper explores the effectiveness of activity-based ethics education strategies across various ICT-related courses. Specifically, an exploratory study was carried out using the Value Cards game (Shen et al., 2021), and running co-design sessions based on the Timelines design activity (Wong & Nguyen, 2021). Acknowledging “the importance of having interdisciplinary teams who create AI ethics content and potentially teach it” (Borenstein & Howard, 2021), we included courses from the Department of Communications and New Media, the Department of Computer Science, and Tembusu College at NUS. More than 120 students from the courses NM2209 “Social Psychology of New Media”, NMC5322 “Interactive Media Marketing Strategies”, CS3240 “Interaction” Design, and UTC1102 “Fakes” participated in the study. All four courses include at least one session that grapples with ethical issues in developing or using technology such as AI. For NM2209 and UTC1102, value cards were deployed to explore the implications of AI-generated content (see Figure 1), for CS3240, adapted value cards were used to discuss the topic of dark patterns such as nudges (see Figure 2), whereas for NMC5322 we used the Timelines design activity (see Figure 3) to explore the impact of various ICTs, such as AI, gamification, and the metaverse, on interactive marketing.
Figure 2. Examples of value cards used in CS3240 (click on the image for a full-sized version).
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Figure 3. Students engaged in the Timelines activity in NMC5322.
Students answered a survey about their ethics perception and awareness before and after participating in the activities. In addition, a subset of the students took part in a focus group soon after the courses ended.
In our presentation, we will share our insights from the use of these two approaches, highlighting the challenges we faced and the strengths of each activity. We will also provide suggestions both for how these approaches can be improved, and what educators can do more broadly to overcome the limitations of current approaches to ICT ethics education.
ACKNOWLEDGEMENTS
This project is supported by the NUS Centre of Development for Teaching and Learning Teaching Enhancement Grant (TEG) “Exploring Instructional Approaches to Develop Students’ Ethical Mindset for a Better Understanding of the Ethical and Social Implications of Technology.”
REFERENCES
Baumer, E. P. S., Blythe, M., & Tanenbaum, T. J. (2020). Evaluating design fiction: The right tool for the job. Proceedings of the 2020 ACM Designing Interactive Systems Conference, 1901–13. https://doi.org/10.1145/3357236.3395464
Borenstein, J., & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI and Ethics, 1(1), 61–65. https://doi.org/10.1007/s43681-020-00002-7
Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and Machines, 30(1), 99–120. https://doi.org/10.1007/s11023-020-09517-8
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504–26. https://doi.org/10.1007/s40593-021- 00239-1
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Shen, H., Deng, W. H., Chattopadhyay, A., Wu, Z. S., Wang, X., & Zhu, H. (2021). Value cards: An educational toolkit for teaching social impacts of machine learning through deliberation. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 850–61.
Wong, R. Y., & Nguyen, T. (2021). Timelines: A world-building activity for values advocacy. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1–15. https://doi.org/10.1145/3411764.3445447
Zhang, W. (2022). Civic AI Education: Developing a deliberative framework. Proceedings of the 4th Annual Symposium on HCI Education (EduCHI’22), April 30-1 May 2022.
