Cultural heritage practitioners and their partners express increased interest in the use of algorithmic methods. They seek to improve collection description and discovery, develop machine actionable collections, and create space for members of their organisations to expand skills and deepen cross-functional community partnerships. Like peers in other sectors, they feel the gravitational pull of machine learning and artificial intelligence, yet they seek to avoid increasingly well documented misuses of these technologies. This talk will advance an argument for the importance of responsible operations in the work that lies ahead. The speaker will draw on his experience leading development of an Responsible Operations: Data Science, Machine Learning, and AI in Libraries; Collections as Data: Part to Whole, and Always Already Computational: Collections as Data.
Zoom Webinar Link