GLAMorous AI Recap: Peer-Reviewed Updates (June–Sept 2025)

First, an apology for the delay in this update — life has been joyfully busy as I’ve just become a new father. Balancing sleepless nights and nappies with heritage data governance and AI hasn’t been easy, but I’m excited to be back with a fresh roundup of what’s been happening in AI and GLAM over the past few months. Thanks for your patience!

Technology is changing how we care for, share, and shape cultural heritage. AI is already part of how we catalogue collections, transcribe records, recommend content, restore artefacts, and interact with visitors. But it also raises deeper questions about ethics, authority, access, and care.

GLAMorous AI (GLAM = Galleries, Libraries, Archives and Museums) is a short, occasional digest for those working in culture, technology, and heritage. It brings you clear, critical, and accessible updates on:

🔍 Tools and projects using AI in creative, critical, or useful ways
📚 Reflections on data, digitisation, and preservation
🧠 Ethical provocations about memory, automation, and trust
🛠️ Practical resources for GLAM professionals
❓ One big question to take back to your team

Whether you work with metadata, exhibitions, public engagement, or digitisation pipelines, this blog is for people making heritage work in a digital world.

🔍 Other Tools & Projects in GLAM

Libraries & Archives: Assessing Real-World AI Maturity
Journal of Library Administration (Aug 2025)
A review of 54 case studies (2018–2024) mapping AI capacity in libraries/archives. Finds strong pilots in metadata and automation, but limited sustainable implementation. Governance and staff skills are the biggest bottlenecks.
📄 Read more here

Cataloguers on GenAI
Journal of Library Administration (Aug 2025)
Explores how cataloguers are experimenting with LLMs for subject analysis and drafting. Recommends clear provenance rules and human-in-the-loop oversight.
📄 Read more here

LLMs for Handwritten Archives
Journal of Archival Science / Taylor & Francis (2025)
Tests prompt-engineered LLMs on handwritten historical documents. Gains in transcription accuracy, but performance still depends heavily on handwriting style.
📄 Read more here

Museum Recommender Systems (DALIR)
Heritage Science (2025)
Presents a scalable interest-driven recommendation model for museum collections. Improves visitor satisfaction and discovery.
📄 Read more here

AI Telepresence Robots for Museum Access
AI & Ethics (2025)
Evaluates telepresence robots in museums with AI support. Strong accessibility benefits, but raises ethical questions around presence and staffing.
📄 Read more here

AI for Experiential Learning in Museums
Smart Learning Environments (Aug 2025)
Shows AI-driven gamification and adaptive experiences improve learning outcomes, especially for young audiences.
📄 Read more here

ReInHerit: AI-Ready Museum Networks
Heritage (MDPI) (July 2025)
Framework for sustainable heritage management, connecting museums with AI-enabled tools for curation and participation.
📄 Read more here

📚 Reflections on Preservation & Data

• Metadata, Markets & AI — AI-optimised metadata risks commodifying GLAM data; calls for public-value metrics.
  📄 Read more here

• AI Across Cultural & Creative Industries — Finds personalisation and analytics as immediate wins, but IP and rights remain unresolved.
  📄 Read more here

🧠 Ethical Provocations

• Bias in Cultural Heritage AI (AI & Society) — Bias enters at every stage, from data selection to interfaces. Practical mitigations offered.
  📄 Read more here

• Generative AI & Cultural Heritage “Expropriation” (AI & Society) — GenAI mirrors historical extractive practices in museums and archives. Calls for community-driven governance and licensing.
  📄 Read more here

• AI, Diversity & Archives (AI & Society) — AI can improve discovery for marginalised collections but also reinforce gaps without curatorial oversight.
  📄 Read more here

🛠️ Practical Resource

Tool: AI-Enhanced Telepresence
A set of pilot-tested protocols from AI & Ethics (2025) for deploying telepresence robots in museums. Offers a ready-made framework for staff training, visitor engagement, and accessibility planning.
📄 Read more here

❓ Question of the Issue

With GLAMs increasingly relying on AI recommender systems, transcription models, and metadata optimisation…
What sort of legacy are we leaving for our descendants — and how will the choices we make today shape how future generations encounter culture, knowledge, and memory?

📖 This Month’s Featured Read

Managing Artificial Intelligence in Archaeology (MAIA)
While not GLAM-specific, this COST Action (CA23141) is building a pan-European hub for AI datasets, tools, and ethics in heritage research. A valuable cross-sector bridge.
👉 Learn more here

💬 About Me

Hi! I’m Alfie—a researcher, writer, and archaeologist working on the digital side of heritage. I’m especially interested in the ethics of AI, open and reusable data, and what happens when modern tech meets ancient stories.

I started GLAMorous AI as a space to explore this without jargon, hype, or 100-page reports. Just thoughtful, practical insights—one post at a time.

Now, as a new father, these questions feel even more urgent. Heritage and data governance are no longer just abstract research themes — they’re about the stories, records, and cultural memory that my child (and future generations) will inherit. The work we do today is, quite literally, about shaping tomorrow’s archive.

✉️ Stay Curious

If this sounds like your thing, I’d love for you to share it or get in touch with a project or idea.

👉 Subscribe or read more at glamorousai.beehiiv.com
👉 Get in touch