Methodology

Co-developed by library professionals and AI experts, the LIBRA.I. methodology is intended to help public libraries address the challenges and opportunities of artificial intelligence in today’s media landscape.

It is divided into thematic blocks that can be read independently or as one coherent document. You, the reader, decide how to best approach your own AI adventure. You can read the full navigable methodology using the following PDF, or access individual chapters on this website. 
 
 

How to Use this Methodology

This handbook provides a practical and adaptable framework for integrating AI into institutional activities. It draws on the experience of the train-the-trainer sessions conducted throughout the project, the expertise of librarians as trusted mediators of information, and the technical and ethical knowledge of AI specialists.

Rather than offering fixed tools, the methodology promotes a flexible, user-centred approach that enables users to tailor activities to their local contexts and audiences. Through a structured yet accessible set of modules, it guides practitioners in understanding AI, adapting existing formats, and developing new learning experiences for citizens.

Tested across three public library settings, the LIBRA.I. methodology empowers libraries to strengthen their role as inclusive learning hubs and supports citizens in critically engaging with AI-driven media environments. While designed for public libraries, the methodology can also be applied by educators and other professionals working with citizens in learning and community settings.The methodology is structured into a series of thematic blocks that can be followed step by step or used independently. Users can move between sections and select the blocks that are most relevant to their needs, experience level, and local context.

The blocks guide practitioners through the full process, from building a basic understanding of AI to identifying audience needs, adapting existing activities, and developing new learning formats. They also support engagement with partners and stakeholders and provide guidance on managing change within the organisation. Each block includes pointers to additional resources and practical materials, such as ready-to-use lessons, printables, and case studies, which can be used directly or adapted to different contexts.

This methodology does not prescribe fixed solutions. Instead, it provides a framework for experimentation, co-creation, and continuous learning. Librarians and other users are encouraged to test, reflect on, and refine their approaches in response to participant feedback and evolving technology.

In addition to the core methodology, an addendum provides further guidance on community building, supporting users in fostering networks, exchange, and collaboration around AI and media literacy.

Whether used by individuals, teams, or as part of training programmes, the handbook aims to empower libraries and other learning actors to act as inclusive hubs, supporting citizens in navigating and critically engaging with AI in everyday life.