Ethics of AI in Education: Towards a Community-Wide Framework

By Wayne Holmes, Kaska Porayska-Pomsta, Kenneth Holstein, Emma Sutherland, T. Baker, Simon Buckingham Shum, O. Santos, Mercedes T. Rodrigo, Mutlu Cukurova, I. Bittencourt and 1 more. International Journal of Artificial Intelligence in Education, 2021

1,019 citations recorded by the source corpus.

While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically, to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community’s leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise the contributions of the 17 respondents, and discuss the complex issues that they raised. Specific outcomes include the recognition that most AIED researchers are not trained to tackle the emerging ethical questions. A well-designed framework for engaging with ethics of AIED that combined a multidisciplinary approach and a set of robust guidelines seems vital in this context.

Subfields: Artificial Intelligence, Computer Science Applications, Safety Research

View Paper: https://www.semanticscholar.org/paper/cfaea43aec271372091aadbc65f089ca67cac8d5

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Citations in the corpus

Ethical principles for artificial intelligence in education (2022, background): “…ethical implications and privacy risks which call for critical attention to differentiate between doing ethical things and doing things ethically (Holmes et al., 2021 ), or as in the words of Russell and Norvig ( 2002 ) “all AI researchers should be concerned with the ethical implications of…”
New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023, background): “However, very few schemes currently exist for the specific issues raised by AI in education [86], except maybe the European Commission Ethics guidelines for trustworthy AI [17] and the forthcoming UNESCO IESALC Manual on AI in Higher Education.”
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions (2023, background): “These tools pose various concerns about their use in high-stakes decisions, including fairness, accountability, explainability, and ethics [120–122].”
Empowering educators to be AI-ready (2022, methodology): “…and how exactly in the system the tool will be used (e.g. Buckingham Shum et al., 2019), the social contexts in which the tools will be used, as well as the ethical (e.g. Holmes et al., 2021) and societal implications related to fairness, accountability and transparency (e.g. Sj ¨ od ´ en, 2020).”
A Documentary Evaluation of Offline AI Integration in Teacher-in-a-Box OER Programmes for Low-Connectivity Schools (2026, unknown): “…learning infrastructure; assessment policy regime (high-stakes dominance versus classroom-based emphasis); governance capacity for local curation and moderation; procurement and data governance constraints relevant to locally hosted systems; and curriculum reform churn [7], [12], [20], [26], [30].”