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The Ethics of Artificial Intelligence in Education: Practices, Challenges, and Debates
Open accessAbstract
The transition of Artificial Intelligence (AI) from a lab-based science to live human contexts brings into sharp focus many historic, socio-cultural biases, inequalities, and moral dilemmas. Many questions that have been raised regarding the broader ethics of AI are also relevant for AI in Education (AIED). AIED raises further specific challenges related to the impact of its technologies on users, how such technologies might be used to reinforce or alter the way that we learn and teach, and what we, as a society and individuals, value as outcomes of education. This chapter discusses key ethical dimensions of AI and contextualises them within AIED design and engineering practices to draw connections between the AIED systems we build, the questions about human learning and development we ask, the ethics of the pedagogies we use, and the considerations of values that we promote in and through AIED within a wider socio-technical system.
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“Crucial AI ethics considerations are equally underexamined in AIEd [60, 103].”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [60]
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BackgroundEthics of AI in Education: Towards a Community-Wide Framework
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., et al. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00239-1 · Cited by 1,437
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“Bias in AI has long been the subject of research, revealing overlapping definitions and different points at which it may enter the AI development and deployment pipeline (Crawford, 2017a; Blodgett, Barocas, Daumé & Wallach 2020; Baker, Ocumpaugh & Andres, 2021).”
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Self-citationBaker, R. S., & Hawn, A. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00285-9 · Cited by 993
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Items 101–105 of 105
The Societal Impacts of Algorithmic Decision-Making
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195 · Cited by 8
Han, B., Ma, Y., Coghlan, S., McKay, D., Buchanan, G., & Smith, W. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790360 · Cited by 3
Williams, A. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2698137 · Cited by 2
Lukianova, L., Symela, K., & Religa, J. (2025) · The New Educational Review · doi:10.15804/tner.2025.81.3.12 · Cited by 2
Algorithmic monoculture and social welfare
(2023) · The Societal Impacts of Algorithmic Decision-Making · doi:10.1145/3603195.3603202
Metadata
- Authors
- Holmes, W., & Porayska-Pomsta, K.
- Affiliations
- University College London (GB)
- ORCID
- Holmes, Wayne
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2022-08-11
- OpenAlex
- W4301626130
- Cited by
- 258
- References
- 53
- Citations by year
- 2026: 66 · 2025: 83 · 2024: 45 · 2023: 59 · 2022: 4
- FWCI
- 67.15
- Type
- book
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Routledge eBooks (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- artificial intelligence in education, AI ethics, educational technology design, educational inequality, pedagogy, educational values, socio-technical systems
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