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 their experience leading development of an Applied Research Agenda, Collections as Data: Part to Whole, and Always Already Computational: Collections as Data.
Thomas Padilla is Practitioner Researcher in Residence at OCLC Research and Visiting Digital Research Services Librarian at the University of Nevada Las Vegas. He consults, publishes, presents, and teaches widely on digital strategy, cultural heritage collections, data literacy, digital scholarship, and data curation. He is Principal Investigator of the Andrew W. Mellon Foundation supported Collections as Data: Part to Whole and Past Principal Investigator of the Institute of Museum and Library Services supported, Always Already Computational: Collections as Data.
This event will be hosted in collaboration with the Digital Cultural Heritage Research Network.
