AI, Research Data Work and Institutional Agility

In this article we investigate the dynamic intersections between Artificial Intelligence/Machine Learning (AI/ML) and research data work, noting the ways in which AI/ML impacts core data standards and principles, and the types and uses of research data. We focus, in particular, on the impact of AI/ML on research data workers. With supporting illustrations in different fields and disciplines, we will investigate how institutions and work practices are impacted by AI/ML in (a) augmenting and amplifying data worker tasks, (b) undermining or replacing tasks, (c) not yet affecting tasks, and (d) shifting identities at work or otherwise changing their relationship to their work. We will also be looking to see if there is evidence of institutional arrangements and work practices where AI/ML technologies are also shaped by research data workers.  Finally, we reflect on the fast-pace of the changing institutional and technological landscape, noting potential disruptions on the horizon to research data work and research data workers.