Speaker: Professor Christopher (Cal) Lee, University of North Carolina
Abstract: Digital collections rest on binary foundations. All digital objects and associated metadata are composed entirely of binary values (bits). Technologies to manage and use digital objects can only perform actions that are reducible to binary values. But archival work involves continuous grappling with dualities. According to Etienne Wenger, a duality is “a single conceptual unit that is formed by two inseparable and mutually constitutive elements whose inherent tensions and complementarity give the concept richness and dynamism.”
Resources are limited, and digital curation professionals cannot pursue all objectives equally. However, rather than simply picking one side of a duality, digital curation professionals must often pursue them (in a parallel or serial form) to varying degrees while ensuring a certain threshold level of commitment to each, finding what Paul Evans and Yves Doz call the “zone of complementarity.” The proper balance depends on a variety of contextual factors that evolve over time. I will focus especially on digital curation dualities relevant to machine learning, including when defining and selecting training data, deciding whether to develop a new model or rely on an existing one, and preserving evidence of machine learning. The dualities of digital curation provide a powerful way to strategize complex, often messy human activities that must be enacted through entirely binary representations.
Bio: Christopher (Cal) Lee is Professor at the University of North Carolina. He has served as Principal Investigator and Co-Principal Investigator of numerous digital curation research and education projects. He is a Fellow of the Society of American Archivists and served as editor of American Archivist.