I am delighted to announce that we have submitted the complete manuscript of the edited collection Navigating Artificial Intelligence for Cultural Heritage Organisations . The book will be published by UCL Press later this year. Here is the table of contents: Introduction Lise Jaillant, Claire Warwick, Paul Gooding, Katherine Aske, Glen Layne-Worthey and J. Stephen Downie Section 1: ‘The Role of AI in Preserving and Making Accessible Digitised and Born-digital Records’ 1. Case Study 1: The National Archives (UK ) Lise Jaillant, Katherine Aske, and Annalina Caputo 2. Case Study 2: Computer Vision and Cultural Heritage Catherine Nicole Coleman 3. Machine Learning at the National Library of Norway Javier de la Rosa Section 2: ‘Text and Beyond: AI applied to Text, Images and Audio-visual Archives’ 4. From Preservation to Access and Beyond – The Role of AI in Audio-visual Archives Julia Noordegraaf and Anna Schjøtt Hansen 5.
I am delighted to be the Principal Investigator of the AHRC-funded project LUSTRE (Unlocking our Digital Past with Artificial Intelligence). LUSTRE seeks to better understand how AI can help improve the preservation, access to and usability of government archives produced in digital form. Much public good could be derived from the analysis of government records, particularly records in digital form. Yet, accessing these data is a complex challenge that requires collaboration across multiple fields and professional sectors to overcome issues including confidentiality, privacy, national security, copyright, technological constraints, and the existence of a multiplicity of different structures, systems and applications. The input of computer scientists who specialise in Artificial Intelligence (AI) is essential to tackling this challenge. Indeed, AI can be used to identify sensitive materials in a mass of born-digital records to make non-sensitive materials accessible. AI can also serve