Conference Agenda

The University of Cambridge’s galleries, garden, libraries, archives and museums hold millions of objects spanning the globe and millennia and representing an unparalleled repository of cultural and natural history. However, challenges such as analogue formats, handwritten documentation, fragmented and dispersed objects, multi-lingual sources and multi-dimensional surfaces render much of this material inaccessible. This paper will introduce the AI for Cultural Heritage Hub (ArCH), a proof-of-concept project led by Cambridge University Library.

ArCH aims to deploy the convening power of the University of Cambridge’s distributed network of collections to create a secure workspace that will empower non-technical users to analyse cultural heritage data with AI tools. Alongside the creation of the infrastructure underpinning the secure workspace (or hub) and an associated community of practice, ArCH is using a series of collections-based case studies to investigate the potential of AI to address three challenges: (1) unlocking inaccessible collections; (2) reconstructing fragmentary and dispersed cultural objects; and (3) integrating expert cultural knowledge into AI algorithms.

After providing an overview of the project, the paper will describe how AI tools were used to convert analogue Cambridge University Library catalogue cards into online records. The Music Department at Cambridge University Libraries and Archives has a plethora of sheaf, card and acquisitions catalogues that currently form a barrier to discovery. During the project, we focussed on trialling and improving prompts for different formats of cards. The primary aim is to develop a workflow that can be scaled up into a large-scale retrospective conversion project.

This presentation explores emerging cataloging challenges surrounding self-published and AI-influenced music scores and recordings, a rapidly expanding segment of library collections. By examining a representative sample of catalog records, the study analyzes how libraries currently describe, classify, and provide access to these non-traditional materials. The findings reveal inconsistencies in metadata practices and a lack of standardized approaches for documenting creative processes involving artificial intelligence and independent production. To address these gaps, the presentation proposes updated cataloging strategies, metadata schema enhancements, and inclusive collection development practices that more accurately reflect the diversity of creators, technologies, and global music communities. Ultimately, this research contributes to advancing professional practice at the intersection of AI, digital humanities, and music librarianship, offering guidance for librarians seeking equitable, transparent, and innovative approaches to representing contemporary music creation in the catalog.

The WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge was adopted in Geneva in May 2024, after a 25-year development process.

So far countries have mainly been concerned about scientific issues such as genetics, but this will begin to encompass music and other cultural expression in the years to come. And the treaty will not come into effect until 15 countries have ratified it.

Meanwhile, the treaty brings up issues about indigenous rights that libraries may have to grapple with in the future:

Does this music belong to an individual author/creator, and therefore can be handled under our standard copyright legislation?

Or does the work belong to a group, iwi, tribe, to a culture? And therefore has no copyright status because it has no identifiable creator, or has even more copyright status, not only that of a creator, but also that of belonging to a group who also have to be consulted?

Do libraries have a role in protecting cultural heritage from exploitation, balancing cultural ownership with public sharing?

Is there any way of navigating international use of indigenous music material, including incorporation in AI tools, and widespread social media exploitation (the 'Kardashian' problem)?