Special Issue
The overall aim of this special issue is to explore how AI can help improve the preservation, access and usability of digital and born-digital archives. It focuses on the perspective and the challenges that AI can offer in unlocking archival data in various sectors (including government).
Bringing together digital humanists and social scientists, AI experts, professionals in Information Management, archivists, librarians, and museum professionals, this special issue welcomes contributions that explore themes including, but not limited to:
_AI applied to archival data created by government, cultural heritage organizations or other institutions;
_“Digital Heap” and the issue of disorganized data;
_Making archival data more accessible for public good;
_Risks associated with AI applied to born-digital records;
_Mitigating these risks: AI and ethics /Designing responsible AI systems;
_Research methods (including AI approaches) to use archival data;
_Qualitative approaches, for example to survey professional attitudes towards AI and archives.
ARTICLE ALREADY PUBLISHED IN THIS SPECIAL ISSUE (AI & Society 2025)
Reusens, M., Adams, A. & Baesens, B. Large Language Models to make museum archive collections more accessible.
Jansen, G., Marciano, R. Developing computer vision and machine learning strategies to unlock government-created records.
Jaillant, L., Mitchell, O., Ewoh-Opu, E. et al. How can we improve the diversity of archival collections with AI? Opportunities, risks, and solutions.
Liu, Y., Heitman, C., Soh, LK. et al. Machine learning methods for isolating indigenous language catalog descriptions.
Canning, D., Jaillant, L. AI to review government records: new work to unlock historically significant digital records.
Vetter, M.A., Jiang, J. & McDowell, Z.J. An endangered species: how LLMs threaten Wikipedia’s sustainability.
McKean, C., Randall, C. Data analysis and network visualisation as tools for curating hybrid correspondence archives.
Green, P. AI and the visualisation needs of researchers using email archives.
Arias Hernández, R., Rockembach, M. Building trustworthy AI solutions: integrating artificial intelligence literacy into records management and archival systems.
The special issue is a key research output of the LUSTRE project funded by the Arts and Humanities Research Council (AHRC) in the UK.