The Role of Data Curation in AI

These are the slides from the 2021 Workshop ‘The Role of Data Curation in AI’, which is part of the series ‘Applying and deploying Artificial Intelligence (AI) in GLAMs’ organised by AI4LAM (Teaching and Learning Working Group) and co-hosted by LIBER and the BnF.

What is Machine Learning and what role does data play? How is the data used to train AI models? What kinds of decisions do librarians make in the process of data curation and how might these impact machine-generated predictions? This workshop will take a project-based approach to explore the importance of data curation in machine learning outcomes.

The speakers will explore how data is thought of in a data science context and how that maps to library practices. Concerns of data bias will be considered including data provenance (What is the history and context of the source material?), defining the boundaries of a data set (Who is in and who is out?) and feature engineering (What is relevant and what is not?).

The aim of the workshop series is to provide training opportunities for those interested in applying and deploying Artificial Intelligence (AI) in Libraries, Galleries, Archives, and Museums. The series will bring together a diverse community of experts with subject and domain expertise, as well as technologists across GLAM institutions for a collaborative learning event to share tools and experiences and to reflect on the process of applying AI and its implications for GLAM institutions.