Scoping AI in EdTech at Edinburgh (SADIE)

SADIE built on the existing knowledge gathered by Learning, Teaching and Web Services (LTW) to understand the current Artificial Intelligence (AI) developments and opportunities available within EdTech (Educational Technology) at the University.  

The aim of SADIE was to allow users to see the progress in the developments of AI tools and features within the University’s centrally supported services that form the AI Innovations Service Release Tracker, and the processes that we use to identify and continually review new and existing tools and features.  

The project also looked at the risks of adopting a particular feature and used the expertise of learning technologists and subject matter experts within Schools across the University, as well as that of the service teams in Information Services, to evaluate these developments and features.

Through SADIE, six primary risk categories were identified in line with the University Risk Policy and Appetite:

1. Bias and Fairness – the data used to train the AI and on which it generates its output are largely unknown;
2. Reliability and Accuracy – AI output is subject to some error -misinterpretation of the data or amplifying mistakes in the data;
3. Regulation and Compliance – data protection and privacy legislation; potential breach of copyright;
4. Ethical and Social – the process that AI uses is not transparent and could be seen as unfair and not aligned with University values;
5. Business – conversely, the University has been at the forefront of AI research and it would seem strange that it did not allow colleagues to innovate with AI;
6. Environmental – a Generative AI approach may require several times the energy of an equivalent non-Generative AI method.

With this knowledge, the project team have created a process, for AI tools and software, that is align with the current processes for the testing of non-AI features that are regularly introduced into our services – to minimise the burden on service teams and allow Schools and Colleges across the University to confidently and securely explore AI for EdTech.

You can find out more about SADIE on the dedicated SharePoint site.

And read reflections on the project from Wesley Kerr, senior Learning Technology Advisor in Educational Design and Engagement, Learning, Teaching and Web Services Division (IS), in the 'SADIE: An approach to managing AI in EdTech services' Teaching Matters blog post.