Ryan Woodward, Assistant Liaison Librarian at Newcastle University
This editorial is based on a lightning talk I delivered earlier this year at the Academic Libraries North conference, where I wanted to take a lighter-hearted approach to some of the anxiety I and many colleagues have been feeling about AI when it comes to librarianship. These are changing and interesting times and it feels like there are a lot of different ways people and institutions are approaching it.
I’m an Assistant Librarian at Newcastle University in the liaison team. My job is teaching, and my job is people. It is entirely student-focused and is challenging but also highly rewarding. I also have a second role: I am my family’s technical support. I am on call 24/7 to answer a wide range of questions about a wide range of technologies that require a decent baseline of knowledge and the ability and curiosity to search for answers. In both roles, I need the ability to communicate complex concepts to users. The big difference is that for library work I must study and actively keep up to date with new resources, literacies, assessments, and best practices through whatever channels I can make time for. As technical support. I use a lot of the same tools and purposes in my own daily life, so I already have understanding gained from using them for fun, leisure, and creative pursuits.
AI and the Library
The advent of the huge leap forward in generative AI was incredible. From seemingly nowhere the playing field changed and the actual applications were right there to play with immediately, not vague reports of possible future technologies, tangible things you could play with immediately. The rapid rate of development was so exciting with new creative doors being flung open, and the chance to be at the forefront of developing brand-new skills like prompt engineering. I registered for accounts, subscribed to mailing lists, and followed key players on social media, adding to my usual information gathering channels, and making it work for me.
AI has become the major talking point in the library sector and you feel the need to develop opinions quickly. Significant conversations are taking place about the impact and ramifications for information literacy, assessment, teaching, critical evaluation, and how staff need to upskill. Not to mention concerns over key parts of our jobs potentially no longer being needed at all. Hello again anxiety, my old friend. Very quickly it felt like you either put your head in the sand or went full tilt trying to lead the adoption of it. It was obvious to most that librarians are well positioned to be leading on AI, as our skillset is getting users to successfully engage with tools critically by having enough contextual knowledge and digital ability. It still all felt a bit chaotic.
Slowing down
When asked for my feelings about AI at one of the many AI-themed conferences and talks I attended this year, I responded that “the overwhelm is real”. This brand-new form of AI, this sea change in academia, brought with it obligations. What do we need to be doing? How guilty should we be If all we’ve done is open, chat GPT and bookmark it? The sheer number of things to read, watch and engage with was paralysing, the feeling of duty that as librarians we must be at the forefront of working out the sector implications and helping develop them. Crumbs. It’s one thing to learn the digital skill of how to use a new tool, it’s another to understand the bigger picture of how a tool can be used. I still open my AI tool of choice and stare at a flashing prompt, it can do anything but generally, I can’t think of anything I want or need it to do. We became flooded with colleagues sharing links, articles, websites, and books. Short video explainers, long-form keynote addresses, communities of practice, training courses, and conferences. I set up an ‘AI’ inbox folder and filtered all the emails into it, destined to remain unread.
How then to overcome this anxiety of it all and find a middle ground between hiding from it or burning out from overwhelm? For me it was treating it like my tech support role, removing the big picture and finding ways to incorporate it into daily practice by lowering the stakes and making it fun where possible. This builds up knowledge organically, and I’ve been able to make connections and contribute to work conversations because I have space to be curious and to search for solutions, rather than feeling I should have known it already. It’s fun to be curious and follow an idea down a rabbit hole or two.
Play and Learn
At the library, we started a staff-focused ‘club’ called ‘AI: Play & Learn’. We meet every few weeks for an hour over lunch, and crucially it is for any interested staff. This means people with different experiences and different purposes come together to share insights and ask questions. We identify a theme for each meeting, such as image creation or lesson planning, and then spend the time chatting, demoing, and playing. Staff have tried tools for the first time, and staff who have used tools share what they did and how. The idea is to build time for creative play and to work to better support innovation without obligation or pressure.
For me, I still wonder what to do with it all, but I found that the more I can make it work for me and the way I learn, the better. I’m trying to use better language: ‘I could’ and ‘I want to’ rather than ‘I must’ or ‘I should’. When there is a problem at work, AI is one of the tools that can be tried, rather than starting with AI and trying to find places to use it.
So what would I suggest, based on my experiences so far? Give yourself time and space to play, with low stakes, find some examples of things people have done with AI and try them yourself. Join or start a club that looks at AI so you can talk to peers about it, but most of all give yourself permission to be silly once in a while.