Pixel International Conferences

Artificial Intelligence (AI) is revolutionising education by promising new opportunities for adaptivity, personalisation, accessibility, and data-driven decision-making [1]. However, beyond the hype, the design, development and application of AI for education must be embedded in ways that enhance rather than impair or compromise human capabilities. To this extent, Human-Centred AI (HCAI) is a branch of Artificial Intelligence which emphasises the central role of the human element in the AI revolution [2]. Consequently, this approach accentuates the need to ensure that AI is transparent, trustworthy, and explainable and that it respects privacy and human rights. This is particularly relevant to education, where the interaction between students, teachers, parents, administrators and all stakeholders remains primarily human in nature. To this extent, this qualitative study aims to explore the perspectives of AI specialists and educators on HCAI for education. A focus group was held with two AI scientists and two educators, and thematic analysis was used to identify and interpret patterns of meaning within the data [3]. The main themes that emerged from this focus group reiterate important current debates in the world of education, from personalised adaptive learning and automated grading to trust, explainability, accessibility and data-driven decision-making. The findings suggest that AI already plays and will keep on playing a major role in underpinning the future of education. Consequently, it must be rooted in a human-centric framework prioritising human well-being, capability and ethics. Possible further research in the area involves examining the impact of human-centred AI in real-world educational settings to understand better the benefits, challenges and limitations that arise during implementation.

Keywords: artificial intelligence, human-centred, education, trust, explainability, ethics

References:

[1] Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.298851

[2] Lepri, B., Oliver, N., & Pentland, A. (2021). Ethical machines: The Human-Centric use of Artificial Intelligence. IScience, 24(3), 102249. https://doi.org/10.1016/j.isci.2021.102249

[3] Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77-101. https://doi.org/10.1191/1478088706qp063oa