Join Information Management Group for our takeover of Innovation Festival!
AI and Cultural Heritage: Critical Reflections and Future Pathways - Thursday 9 October, 9:30 - 5:00pm (BST)
This session will explore the increasing role of artificial intelligence (AI) in the cultural heritage sector, highlighting both the opportunities it presents and the challenges it raises for professionals, institutions and public sector bodies. We invite case studies that critically examine the use of AI in areas such as interpretation, reporting, digitisation, conservation and improving the discoverability and usability of heritage resources. Submissions should consider the broader implications of their work on future research, industry standards, and ethical practice. The session aims to encourage dialogue on responsible innovation and sustainable integration of AI across heritage sectors.
Part one - 9:30 - 12:30 Case studies
Delivered by Holly Wright, Archaeology Data Service, Anthony Corns, The Discovery Programme, Laura Hone, Historic Environment Scotland, Evie Brown, Welsh Government and Tom Elliot, Historic England
Timings and topics
09:30 Welcome by Information Management Group Chair and session organiser, Laura O'Connor, Historic Environment Scotland
09:35 - 10.00 Introduction of the COST Action Managing AI for Archaeology (MAIA): building a community of practice - Holly Wright, Archaeology Data Service
10:00 - 10.25 The ADAF Tool: Using machine learning in the detection of archaeological monuments in ALS data - Anthony Corns, Discovery Programme
10:25 - 10.35 Q&A
10:35 - 10.45 Short break
10:45 - 11.10 Protecting Our Winged Draculas: Modelling Bat Roost Suitability using Clustering and MaxEnt - Laura Hone, Historic Environment Scotland
11:10 - 11.35 Using AI to create a dataset of historic woodland in Wales - Evie Brown,
11:35 - 11.45 Q&A
11:45 Using Machine Learning to conduct lithic sourcing of Mesolithic artefacts from the Lower Wye Valley/ Welsh Marches – Tom Elliot, Historic England
12.10 - 12.20 Q&A
12.20 - 12.30 Opportunity for some summary discussion
Part two - 2:00 - 5:00 Panel discussion
Chaired by Laura O’Connor, Historic Environment Scotland with panellists Anthony Corns, The Discovery Programme, Holly Wright, Archaeology Data Service, Ben Wallace Warwickshire County Council (ALGAO HER Committee), Robert Sutton, Cotswold Archaeology, Laura Hone, Historic Environment Scotland, Tom Elliot, Historic England and Evie Brown, Welsh Government.
Discussion themes
Artificial intelligence (AI) is opening up new opportunities across the heritage sector - from uncovering previously hidden trends in archives and collection to creating immersive experiences that compellingly bring the past to life. However, these innovations also raise complex questions about authenticity, ethics and accuracy. This panel will explore how AI can be used responsibly to support research, storytelling and community engagement, while also safeguarding the vital human expertise and perspective that are foundational to its use. We will examine how AI can augment - rather than replace - the human experience that underpins meaningful heritage engagement.
CIfA's Information Management Special Interest Group represents the interests of professionals who work or have an interest in the area of information management. The group aims to promote standards and good practice relevant to the management of all aspects of historic environment and wider heritage sector information through the activities of the CIfA.
The group focuses on how those working in the historic environment/ heritage sector create, access and share digital data together with the standards involved in these processes. Our work relates to
- data capture and recording practice
- recording system design
- archiving of digital data
- promoting access to information
- re-use of digital archives
The Information Management Group works to coordinate, develop, maintain and promote standards for the recording of heritage information, to promote best practice and share experience in the application of information standards, and promote and seek involvement in the future development of existing data standards.
