LIBRA.I. METHODOLOGY HANDBOOK: Using Artificial Intelligence for Media and Information Literacy in Public Libraries
Showcasing How Libraries Can Make AI Literacy Human, Practical and Inclusive – the LIBRA.I. Methodology Handbook is intended as a practical roadmap for librarians and educators navigating the age of AI.
Artificial intelligence (AI) is no longer a distant or new technological trend; it has now reshaped the information ecosystem. This is why public libraries have had to respond to this pressing situation and consider how they can help citizens engage critically and confidently with this new reality.
The methodology is not simply a handbook on AI literacy but a practical philosophy for how libraries can approach it while remaining rooted in their core values: trust, inclusion, critical thinking, and public service. What makes LIBRA.I. distinctive is that it does not treat AI literacy as a technical training problem. It treats it as a social and educational practice. Rather than offering a rigid curriculum or prescribing a single way to teach about AI, the methodology invites experimentation. It was developed through collaboration, testing and reflection; shaped in train-the-trainer bootcamps, refined in public library settings, and grounded in the lived realities of librarians working with communities. This makes the methodology feel less like a manual and more like a framework that grows with those using it. Creators were guided by the idea of it being used rather than left on a shelf. Its starting point is simple but powerful: libraries do not need to become technology labs to engage with AI. They can build on what they excel in: supporting learning, fostering dialogue and helping people navigate information critically.
A METHODOLOGY BUILT IN BLOCKS, NOT SILOS
The methodology is organised as a series of interconnected blocks, but these are not meant to be followed mechanically. They function more like building materials that practitioners can combine as needed. It begins with the fundamentals, helping users understand what AI is, where it appears in everyday life, and the risks it poses, including bias, misinformation, and privacy concerns. But this foundation is not intended to turn users into technical experts. It exists to create confidence. From there, the focus shifts quickly from technology to people.
One of the methodology’s strongest dimensions is its emphasis on knowing your audience. Whether working with seniors vulnerable to disinformation, young creatives experimenting with generative tools, or adult learners who are curious but cautious about AI, the methodology insists that effective AI literacy starts with listening. Understanding needs comes before designing activities. That human-centred approach runs through the entire framework.
START WITH WHAT ALREADY EXISTS
Perhaps the most refreshing idea in the LIBRA.I. methodology framework is that libraries do not need to invent entirely new programming to engage with AI literacy. Instead, the methodology encourages something much more realistic: adapt what already works. A creative writing workshop can become a space for exploring authorship in the age of generative AI. A digital skills class can open a discussion about algorithmic bias or deepfakes. A cultural heritage activity can incorporate experimentation with AI tools. This principle, enhancing rather than replacing existing formats, makes the methodology highly accessible, especially for libraries working with limited time and resources. It lowers the threshold for action; AI literacy becomes less a new institutional burden and more a new lens through which existing work can evolve.
LEARNING THROUGH PRACTICE, NOT THEORY ALONE
The methodology is strongly practice-oriented. Its lesson plans and workshop formats are not designed as static templates but as adaptable prototypes. They encourage facilitation rather than lecturing, and experimentation rather than passive instruction. This reflects a deeper educational philosophy: people understand emerging technologies best by engaging with them critically and collectively. That is why the methodology values reflection exercises, hands-on testing, dialogue, and even small “micro-experiments” with AI tools.
The message is clear: confidence does not come from knowing everything about AI. It comes from learning how to ask good questions.
ETHICS IS NOT AN ADD-ON
Another defining strength of the methodology is that ethics is not isolated into a single chapter or compliance checklist. It runs through everything. Questions of bias, data protection, source verification and transparency are woven into the methodology as everyday practice, not as abstract debate. Especially powerful is the principle the handbook repeatedly returns to: put human intelligence first. At a time when conversations about AI often swing between hype and fear, this is a grounding idea.
The methodology does not position AI as something to be either embraced uncritically or rejected outright. Instead, it frames AI as something citizens need help understanding, and libraries as places where that understanding can be developed responsibly. That is a much more refined perspective of AI literacy.
CHANGE HAPPENS THROUGH SMALL STEPS
Another compelling aspect of the methodology is its realism and recognition that institutional change rarely happens through big innovation strategies. It happens through small, credible experiments.
- A pilot workshop.
- A conversation with stakeholders.
- A lesson adapted for a familiar audience.
- A staff team testing one AI tool together.
These modest actions are treated not as preliminary steps towards “real” transformation, but as the transformation itself, making the methodology feel practical and empowering rather than overwhelming. That matters especially for public libraries navigating scarce resources and competing priorities.
LIBRARIES AS DEMOCRATIC SPACES FOR AI LITERACY
Perhaps the most original contribution of the LIBRA.I. methodology is its reimagining of the role of libraries. It does not present libraries as places merely responding to technological change but as active civic spaces where people can make sense of that change together which is a a profound shift. In this view, AI literacy is not just about teaching people to use tools. It is about strengthening critical judgement, supporting informed participation and helping communities navigate technological change on their own terms. And that is very much library work.
WHY THIS METHODOLOGY MATTERS NOW
There is no shortage of resources explaining AI, what is rare are methodologies that ask how communities can learn about AI in ways that are ethical, inclusive and grounded in public values. That is where LIBRA.I. stands out as its innovation lies not in introducing spectacular new technologies, but in showing how trusted institutions can respond to technological change without losing sight of human needs. It offers something urgently needed right now: a model of AI literacy that is critical without being fearful, practical without being instrumental, and innovative without forsaking social responsibility.
Tēma: Mākslīgais intelekts
Autors: Latvijas Nacionālā bibliotēka
Gads: 2026
