Beyond the algorithm: Developing a culturally responsive and ethically sound AI policy in schools
Written By: Author(s): Ryan Green
5 min read
RYAN GREEN, DIRECTOR, EMERALDS INTERNATIONAL SCHOOL, PORT SAID, EGYPT
Recent research provides useful frameworks for evaluating the risks and responsibilities involved in adopting AI (artificial intelligence) in schools. Floridi and Cowls (2019) offer principles such as fairness, accountability, and explainability; relevant when assessing tools that automate grading or flag student behaviour. Chelladurai and Bhatia (2023) urge school leaders to interrogate how AI systems function in context, rather than accept them at face value. Heffernan (2022) stresses that digital decisions shape inclusion and equity, particularly in diverse school settings. However, much of the existing literature remains theoretical, with limited guidance on how schools should apply these principles to specific platforms or decision points. There is a gap between ethical frameworks and practical implementation particularly in international schools operating across multiple cultures, curricula and regulatory cont
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References
- Alan Turing Institute (2021) Understanding algorithmic fairness in education. Available at: https://www.turing.ac.uk/research/research-projects/algorithmic-fairness-education (accessed: 9 May 2025).
- Chelladurai R and Bhatia V (2023) Leading ethically in the age of AI. Journal of Educational Leadership and Policy. 38(2): 112–127.
- Department for Education (2023) Safeguarding and remote education during coronavirus (COVID-19). Available at: https://www.gov.uk/guidance/safeguarding-and-remote-education-during-coronavirus-covid-19 (accessed: 9 May 2025).
- Floridi L and Cowls J (2019) A unified framework of five principles for AI in society. Harvard Data Science Review. 1(1). DOI: 10.1162/99608f92.8cd550d1.
- Heffernan A (2022) Leadership for Inclusive Digital Schools: Ethics, Equity and Education Futures. London: Routledge.
- Luckin R, Holmes W, Griffiths M and Forcier L B (2016) Intelligence Unleashed: An Argument for AI in Education. Pearson Education. Available at: https://www.pearson.com/content/dam/one-dot-com/one-dot-com/global/Files/about-pearson/innovation/open-ideas/Intelligence_Unleashed_Publishing.pdf (accessed: 9 May 2025).
- Selwyn N (2023) Should Robots Replace Teachers? AI and the Future of Education. Cambridge: Polity Press.
- UNESCO (2021) Artificial intelligence and education: Guidance for policymakers. Paris: UNESCO. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000377071 (Accessed: 9 May 2025).
- Williamson B and Eynon R (2020) Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology. 45(3): 223–235. DOI: 10.1080/17439884.2020.1795415.
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