A UK perspective on responsible education for responsible AI: a multidisciplinary review and evaluation framework

Responsible Artificial Intelligence (RAI) education has emerged as a way of approaching the field of AI to address a host of concerns (Bentley et al., 2023). Many education providers have been releasing new RAI-related online courses, programmes, or toolkits. When combined with the issues emerging from the development, deployment, and use of AI, the expansion of RAI education and the proliferation of resources raise two critical questions. First, what can we learn about RAI from examining both the content and structure of publicly available RAI educational resources? Second, how might we understand the quality and impact of these RAI resources? We conducted a systematic search of UK RAI educational resources found online. We first present a descriptive analysis of 211 resources collected, including their type, format, cost, sector, audience, and type of provider. Furthermore, we describe our collaborative approach to analysing four pre-selected resources in-depth, from which we outlined an evaluation framework that we then employed for assessing the content of a subset of 47 resources. The five crucial areas of our framework could guide both learners and developers when approaching RAI resources.

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Publication Details

Journal
Journal of Responsible Technology
Published
2025-12-27
DOI
https://doi.org/10.1016/j.jrt.2025.100147
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

A UK perspective on responsible education for responsible AI: a multidisciplinary review and evaluation framework

Christine Aicardi, Brian Ball, Caitlin Bentley, Oana Andrei et al.
Journal of Responsible Technology
Ethics and Social Impacts of AI
article

A UK perspective on responsible education for responsible AI: a multidisciplinary review and evaluation framework

Christine Aicardi, Brian Ball, Caitlin Bentley, Oana Andrei, Maira Klyshbekova, Mohammad Naiseh, Stef Garasto, Amy Aisha Brown, Gisela Reyes Cruz
article en

Abstract

Responsible Artificial Intelligence (RAI) education has emerged as a way of approaching the field of AI to address a host of concerns (Bentley et al., 2023). Many education providers have been releasing new RAI-related online courses, programmes, or toolkits. When combined with the issues emerging from the development, deployment, and use of AI, the expansion of RAI education and the proliferation of resources raise two critical questions. First, what can we learn about RAI from examining both the content and structure of publicly available RAI educational resources? Second, how might we understand the quality and impact of these RAI resources? We conducted a systematic search of UK RAI educational resources found online. We first present a descriptive analysis of 211 resources collected, including their type, format, cost, sector, audience, and type of provider. Furthermore, we describe our collaborative approach to analysing four pre-selected resources in-depth, from which we outlined an evaluation framework that we then employed for assessing the content of a subset of 47 resources. The five crucial areas of our framework could guide both learners and developers when approaching RAI resources.

Journal of Responsible TechnologyVol. 25
Northeastern University (US), University of Nottingham (GB), King's College London (GB), University of Aberdeen (GB), King's College School (GB), University of Greenwich (GB), University of Portsmouth (GB), University of Glasgow (GB)
Engineering and Physical Sciences Research Council
Quality Education
Openalex Percentile: Top 27%
Ethics and Social Impacts of AI
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