This guest post is by Isabell Seeger, a soon-to-be MLIS graduate with a career background in linguistics and AI. In this blog post, she outlines her motivation for a career change from tech into librarianship - and the surprising parallels and transferable skills from one to the other.
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| Isabelle Seeger by the author, an artist's illustration of artificial intelligence by Google DeepMind from Pexels and close-up shot of books on a bookshelf by Mikhail Nilov via Pexels |
Introduction
A year ago, I was a linguist who worked in AI, building language datasets and evaluating AI model output. Fast forward to now, and I am about to graduate with a MLIS degree from University College Dublin, getting ready for a career that may look very different on paper - but feels surprisingly aligned in practice. In this post, I wanted to share a bit about how I made the switch from tech to librarianship, and why I think this career pivot actually makes a lot of sense.
So, What Does a Linguist Do?
In Tech, my job was “teaching computers how to read and write” - my go-to tagline for parties where “computational linguist” would get polite but slightly confused nods. In practice, this meant creating model training data and running large-scale human evaluations to make sure that language-based AI systems met quality benchmarks and provided value to users. On a platform as large as LinkedIn, my previous employer, this often meant projects and products that were seen and used by millions of people. When I started my job, we were focused on Machine Learning models - now often called “traditional AI”. When ChatGPT came around, my role profile changed to include LLMs (Large Language Models), and we all became prompt engineering experts on the side.
Overall, it’s hard for me to sum up the role of a tech linguist, as we often wore many hats - project manager, technical writer for data annotation guidelines, data wrangler and analyst for data and model insights, and metadata expert for ontology and schema design, to name just a few. Which brings me to the next bit:
Switching to Librarianship
Working in tech gives you a front row seat for the work and money that goes into building AI systems, and just how ubiquitous they are in all our daily lives, whether we are aware of them or not. I always viewed my role as the “human in the loop” - crucial to ensure trust and quality. In the private sector, especially with mounting economic pressures, I slowly felt a noticeable shift from quality to quantity, from care to speed, from human review to “Can we do this with AI instead?” - a fair question to ask (I am not a Luddite - I am just a critical thinker), but more often than not, my inner voice had a resounding “no” as an answer, not always welcome.
A huge part of linguistic work in tech is making information digestible for AI systems, starting from representative data sampling to explicitly adding labels to data that goes into model training. The leap into information architecture is short, and many of my colleagues in similar roles (such as taxonomy) have a librarianship background. I found myself wanting to go the other way, to learn more about the values I associated with librarianship such as equal access to knowledge, and being intentional about the ethics of being an information professional - not just building systems, but thinking holistically about their impact. Surrounded by the questions of what we could do with information, I wanted to ask what we should do with it - and sometimes, if we should at all.
Back to School
As my decision to change careers solidified, I had to make a few decisions. Personally, I wanted to stay in Dublin (why Germans love Ireland is a topic for another post), and was delighted when I found the MLIS degree offered at UCD. In fact, my excited grin when reading the syllabus was probably all the decision-making fuel I needed.
Going back to school after working full-time for 6 years was humbling, but also refreshing. This is my second Master’s degree, and I can say that I approached it with more sincerity and diligence - I knew what I wanted to get out of it, and wanted to learn as much as I could. I organised my reading lists early, took copious notes, attended events, and audited several modules on top of my core curriculum to make the most of the limited time (one year is surprisingly short). I loved being able to organise my time more freely, meeting wonderful new people, and having insightful conversations about topics that mattered to me. It is a very gratifying experience to connect with people who care about similar things, and I deeply value my new friendships and budding professional network.
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| First-person perspective studying in UCD's James Joyce Library, showing an iPad, comfy seating, and a water bottle. Picture credit Isabell Seeger 2024. |
Progressing through the curriculum, I realised more and more how transferable many of my tech skills were to the LIS space. Whether it is thinking about metadata for digital libraries, planning quantitative or qualitative research methodologies, or designing literacy instruction programmes - many of my “tech linguist” hats are applicable.
I was pleasantly surprised by the presence of technology-focused modules on the course, and attempts to bring AI to the classroom even in more traditional LIS areas such as cataloging. I strongly believe librarians need to be tech-literate. Using tools does not mean using them uncritically; in fact, I think informed and critical use of tech (be it ChatGPT or social media) is paramount for being a part of today’s society. Especially as librarians, we need to stay ahead of the curve, so we can provide AI and digital literacy instruction to people who need it.
The diverse background of people in my MLIS cohort was something I cherished deeply. I believe this is one of the strengths of the LIS sector - many of us come in through non-traditional pathways, and we can learn so much from each other by sharing our experiences and knowledge. I hope I will be able to bring fresh perspectives into my future roles in librarianship, and continue to be able to draw on previous experience to inform future thinking.
Looking Ahead
So, what kind of librarian do I want to be? As I reflect on my year of learning, I see a few pathways for myself. I want to keep my focus on technical and digital spaces - building a small digital library project was one of my favourite class assignments this year. As is probably no surprise, I am also passionate about AI literacy (here is another class project), and would love to help more people develop AI skills and critical thinking as they engage with tech and AI in their everyday lives.
Learning about the area of Research Data Management within academic librarianship got me really excited - having previously designed, collected, analysed, and stored various datasets in my linguist role, I feel a lot of my experience is applicable to RDM. I also love the idea of supporting research, and being able to contribute to open data and open scholarship.
Additionally, I was lucky to recently complete a 4-week internship in the Research Services team of the TU Dublin library, and I had a wonderful time learning about institutional repositories, research information management, and open research. I think my tech skills lend themselves well to a role in academic librarianship, but I am keeping my eyes and mind open, and am hopeful for my professional future, wherever it will lead me.
Some Takeaways
(Tech) linguists and librarians have a lot in common:
We are the human in the loop, making connections from raw data to structured knowledge
Many of the technical skills from the tech space are applicable (and desired!) in librarianship - we love a good spreadsheet
When you tell people your job title, they have no idea what you do, but they think it sounds really cool.
If you are a fellow career changer, or have any questions or thoughts, feel free to email me via isabell.seeger@email.de, or connect with me on LinkedIn - old habits die hard!
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