OUR AI

A new Library Directorate for Artificial Intelligence and Ideas Adoption

The creation of the new Artificial Intelligence and Ideas Adoption (AIIA) Directorate has provided a mandate for the Library to explore the application of AI in support of teaching, learning, research and the underpinning processes of a forward-looking academic research library.  Internally, AI engagement efforts have included practical and thought-provoking AI sessions at the Library’s Together24 staff conference.   

To further the Library’s ambition within the University, we are also engaged with Sister, Manchester’s new innovation district and neighbourhood.  We have built foundational relationships with Bruntwood Sci-tech and the Turing Innovation Catalyst (TIC).

There is a concerted effort to identify external partners with whom to share our thinking and develop proof-of-concepts. This has been achieved through workshops and presentations at events for Society of College, National and University Libraries (SCONUL), Research Libraries UK, (RLUK) Chartered Institute of Library and Information Professionals, (CILIP), and Academic Libraries North (ALN).  

Through 2025, AIIA will be working with all parts of the Library and the first inhabitants of Sister. We aim to design new services for the neighbourhood and identify new routes for community engagement and widening participation.  

Transforming Office for Open Research operations through AI

The Office for Open Research has been actively exploring breakthroughs in generative AI tools, with a primary focus on our Research Metrics Team. By prompting Large Language Models, we've developed powerful scripts that significantly boost the team's capabilities and capacity. These AI tools have enabled us to consolidate a wide range of information about the University's research activities and impact into a single dataset, called the Mosaic.

This has already provided valuable insights, such as identifying which University communities most frequently collaborate with low and middle-income countries. The Mosaic will help us build on our success as the top-ranked university in the UK and Europe, and second globally for social and environmental impact in the 2024 Times Higher Education (THE) University Impact Ranking.  

We are also exploring how AI can transform our operations within the Office for Open Research. One outcome is a new system that streamlines Open Access payment management. The team will continue to explore how these revolutionary tools can further enhance our efforts to foster a more open, reproducible, and responsible research environment at the University.  

Academic integrity and AI support

Building on our success from last year, the Library continues to shape The University of Manchester’s approach to reflecting on, supporting and integrating Generative AI (GenAI) tools into teaching and learning.  

This is exemplified by the Library’s significant contribution to The University of Manchester AI Teaching Guidance, ensuring our expertise was reflected in this critical resource.  Our FAQ 'Can I use a chatbot or AI tool in my assignments?' was the most viewed FAQ of the year with a total of 9,000 views.   

The Library also led the creation of a cross-university online guide to Academic Integrity for students, now part of our My Learning Essentials support. This interactive guide provides comprehensive guidance on using GenAI tools for learning and assessment,  reframing academic integrity, and encouraging reflection and a deeper understanding of University expectations and rules.

GenAI guidance and support has been integrated into Library teaching, emphasising the importance of using AI as a tool to support, rather than replace, learning. Students are encouraged to reflect on key questions regarding the use of GenAI tools in their studies, in all our My Learning Essentials workshops. To further support this we have developed an accompanying checklist for students and a blog post for trainers to explore these concepts further.  

Improving skills and testing AI ideas

The Library has been working with IT Services and Research IT teams to improve their skills and test how AI can be used in real-life situations.   Some of their experimental work includes:  

• Using machine learning to sort and group uncategorised images into collections.  
• Applying GenAI to help with accessibility issues: GenAI can create text, images, videos, and more based on prompts. It learns patterns from the input it receives and then generates new content following those patterns. One project has focused on creating descriptions for images.  
• Streamlining archival workflows: Colleagues working on the Elizabeth Wilson Collection recently published their first archive collection records, acknowledging assistance from Generative AI.  

Meanwhile,  Microsoft CoPilot has also been undergoing tests in the Library as part of an institution-wide pilot. Alongside this, the Library has also been testing AI capabilities being built into new and existing platforms, particularly scholarly search tools such as ProQuest One and Primo Assistant.  

Robotic processing

In order to streamline processes and automate tasks to ensure we are working to maximum efficiency, cross-team collaborations have been exploring how to use Robotic Process Automation to automate the process of gathering usage data. The impact of this collaborative work is significant, and this will save Library staff considerable time.