SLA conference 2025 (M25 consortium) – Jonathan Winter, Attendee.
London College of Fashion, Queen Elizabeth Olympic Park, Stratford.
June 19th 2025
Visiting the school of fashion felt a bit like being in the Guggenheim museum in New York or the NT or Barbican Centre.
There was Lot of curved concrete and dressmakers’ dummies dotted around. I saw serious students looking much like the exhibits.
I felt that in an impressive space such as this, students naturally behave and work harder and are inspired. I came away feeling thoroughly energized. The space was clearly designed for users unlike all other libraries I have been in. I would welcome being corrected on this.
The concrete minimalism seemed designed as a blank canvas to inspire. The library on level five sits organically in the space as it is hard to know where the library begins and the rest of the building ends.
The librarian took us on a tour of the collection including two exhibits. Impressive, was a decolonizing fashion waistcoat with African patterns and a tactile area for different sustainable materials sitting on a recycled table made from 40000 bottles.
The electric archive shelves move side to side for access much as ours do, but of course with a fancy safety mechanism so as not to harm users. Here, a rare journal full of an artist’s collages was unboxed.
There were many fashion journals on shelves dotted around the area, added to the feeling that we were in an art gallery or a museum of sorts.
Kindly, M25 got to use the two rooms for free and most importantly more could be spent on food. Lunch was delicious and Summery: Roast pumpkin, fennel and green bean salad, lemon chicken, puy lentils with feta and pizza.
Professor Julie Wall from the University of West London is an expert on AI. She opened the day with a talk on practical and ethical AI [considerations] in a changing library landscape.
‘Be aware AI is not neutral’, she warned. When you use it, it can be quite generic and biased by the nationality of the country that made it.
AI also doesn’t know how to say: ‘I don’t know’. Sometimes it will make up a fictitious reference list. Its rationale is that it knows that the best essays have reference lists, so rather than not having one, it will make one up. It gives us what it thinks we want. It is predictive. For example, when asking AI for a picture of successful university students, it generated the students in a lecture simultaneously wearing their graduation clothes.
This all made me realize how negatively I felt towards AI. I unconsciously felt that today’s students are lazy and think they can bypass real work by using AI. I had this belief that AI is destroying universities and taking away authentic voices as it can do everything better than humans. However, as the day went on, I gradually came to the conclusion that AI is a tool that when used correctly can be a great assistant. Furthermore, AI, widely used by students, is something I must learn to more effectively support students rather than an ‘I-know-best’ attitude.
There are many AI’s available, and Professor Wall recommended Microsoft Co-pilot as slightly more reliable. Our university pays Microsoft for a license, so the data is slightly better protected.
The last session was led by LC Chung, a teaching and learning librarian from Kings College, University of London. They facilitated a good training session where we used AI within the PREPARE framework. As we saw, AI is quite generic at first, and searches need to be refined.
The PREPARE framework
Prompt: Start with a clear question. Provide a stage for what follows.
For example, “Write a summary about the latest AI trends in education.”
Role: Give the AI a role and outline the context.
For example, “You’re an education expert analyzing the AI trends.”
Explicit: Be specific in your question to avoid misunderstandings.
For example, “In the summary, mention how AI can contribute to personalized learning.”
Parameters: Set clear frameworks such as tone of voice and the format of the output.
For example, “Use an informative tone and keep the summary under 300 words.”
Ask: Ask the AI to ask you clarification questions before it continues.
For example, “Ask me some clarification questions first, and then answer.”
Rate: Ask the AI to rate its own output.
For example: “Give the summary a rating based on 0-10 points, and indicate what could be improved.”
Emotion: Add an emotional stimulus. This appears to be able to increase quality.
For example: “Breathe in, and breathe out. Try to really do your best. It’s important to me.” If you get emotional then AI does better!
He suggests to give one extra tip: ask the AI to make thinking steps explicit.
For example, “Take this task one step at a time, and explain your thinking steps.”
AI Pioneers Partners (2025) The Prepare Framework. Available at: https://aipioneers.org/the-prepare-framework (Accessed: 20th June 2025).