Special Issue
Special Issue on When Data turns into Archives: Making Digital Records More Accessible with AI, in AI and Society
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.
IMPORTANT DATES:
Abstract submission: 30th June 2024
Manuscript submission: 30th September 2024
For inquiries and to submit your abstract (300 words) by email, please contact l.jaillant[at] lboro.ac.uk
Please find the call for papers here https://link.springer.com/journal/146/updates/26671434
The proposed special issue is a key research output of the LUSTRE project funded by the Arts and Humanities Research Council (AHRC) in the UK.