Facing the Future: Machine Learning and AI in Libraries, Archives and Museums

Every week brings a new headline about AI, or ‘artificial intelligence’. Major search engines and social networks are competing to integrate AI, despite serious concerns about inaccurate results from AI chat bots.

In the last year alone, significantly improved AI, machine learning (ML) and data science tools have changed how information is processed and generated. ML and data science methods have the potential to connect library collections,  and to enable better discoverability and support innovative research. But libraries, archives and museums (GLAMs) face challenges in finding resources to meet AI-hyped expectations, and in implementing new forms of information provenance and digital preservation. How will changes in AI externally change expectations about GLAMs? And how can we build on what we already know about the role of technologies in cultural organisations to think strategically about integrating AI into GLAM work?

An invited lecture for the Hong Kong University of Science and Technology Library, School of Humanities & Social Science. Audience included postgraduate students in Professional Development for Research Postgraduate Students, Alumni, Faculty and staff, General public, HKUST Family, PG students, UG students