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This house believes that Education has control of the technology, policy and processes being used (Part 2 of 2)

The second part of the report on the live debate on (learning) technologies and Artificial Intelligence (AI) hosted by the ALT East England (ALT EE).

by Uwe Richter, Neil Dixon (Anglia Ruskin University), Rob Howe (University of Northampton)

This blog post concludes the debate to discuss the rapid pace of AI and related technologies and the extent to which institutions were still in control. 

This post concludes the question is AI a gift?, and discusses keeping up to date with professional development and reports on the final vote on whether education has control over technology. 

In the first blog post, the panel discussed is AI a curse?, with possible issues such as copyright, lack of AI explainability and possible bias. AI could also be interpreted as a gift. Many recent AI releases appeal to those who are time poor, and/or need additional assistance. The freemium model which allows free limited access to user-friendly functionality has encouraged millions of sign-ups. These users will view the systems as a gift to assist with work which may have taken time and effort to create. The integration in core productivity suites such as Microsoft 365 (such as Microsoft Co-Pilot) means that some functionality will be available without any further cost or sign-up. Students will use these tools with assignments set by institutions; researchers will use them to analyse data or conduct literature reviews; academic staff will use them to create new teaching resources; senior and professional staff will use them to create or summarise long documents. 

Finally, the two groups considered how we keep up with training/continuous professional training (CPD) as new policies or procedures are implemented. Staff and students do need to learn how to use technology to be digitally literate.  Otherwise, the risks are that technology is poorly used or misused(e.g., it was noted that there is a need to enhance AI digital literacy). There are many issues concerning the training and CPD around Chat GPT. It was noted that GDPR restrictions have meant that technology has been limited in certain countries. This encourages people to find and use the technology themselves rather than adopting solutions within the university.

Another challenge is that academics do not always have time for safe spaces to test these technologies. Although the training may be available, staff do not always have the time to prioritise this level of training.

However, education needs small groups of people who can go out and experiment, who are the innovators, testers and early adopters of new technologies. We need this group in every institution to  figure out how to use new tools. 

“if you’ve got a question, come and see us, come and talk to us. We’ll help you understand that technology. I think you need that small group in every university. That’s the best starting point. It’s ‘cause you always gonna have you always find those people [who] are interested in it” (Panel member)

Additionally, universities can customise some AI tools around their own rules. Technology evolves and universities need to invest more in their technological infrastructure such as data processing, so we can keep up. An example of data processing and categorisation is Named Entity Recognition which 

is a form of natural language processing (NLP) that involves extracting and identifying essential information from text. The information that is extracted and categorised is called entity […] NER essentially extracts and categorises the detected entity into a predetermined category (Turing, 2023). 

Modern AI uses complex algorithms to process and make sense of data. As universities generate more and more data, AI is increasingly required to make effective use of the data.

A final poll from the session indicated that participants felt that institutions had lost control of policies and processes due to the rapid pace of change during 2023. Teams are moving rapidly to put interventions in place which will impact forthcoming developments (these include upskilling staff and students on AI digital capability, and remodelling the assessment process to ensure academic integrity is maintained). As technology development rapidly accelerates, it remains to be seen whether institutions manage to catch up or whether new technology challenges will ensure that they are elusively out of reach.

ALT EE would like to thank all the debate panel members, both staff and students, and the debate moderator Michael Webb for making the event happen and their engaging discussions. 


Turing (2023). A Comprehensive Guide to Named Entity Recognition (NER). Available at: https://www.turing.com/kb/a-comprehensive-guide-to-named-entity-recognition (Accessed 17 October 2023)

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