Critical Data Practices in Humanities Research

This workshop explores the unique challenges that face the arts and humanities as we ground data-driven insights in real-world human complexity, and in various social, cultural, and historical contexts. Digitization and computational methods provide new opportunities for understanding the cultural implications of data, its meaning, and its significance to the long history of recorded human experience. We must therefore carefully consider the ways that we derive meaning from data through critical attention to methods and sources. The workshop gives particular attention to what the humanities have to say to data practices in the current moment and urges us to critically examine the issues of representation, equity, accessibility, and discoverability. Computational and Data Sciences approaches are running against the tensions between the urge to generalize data for the purposes of standardization and prediction, and the need to recognize the significance of the individual and the specific. Critical voices in these same disciplines are beginning to point to algorithmic bias and marginalization that have shaped new technology, while current work in law and policy studies asks whether fairness can be calculated and automated in civil society. How does the adoption of data-driven approaches in humanities research inflect these matters, and how can insight from humanities critiques impact the fields of computational data sciences? The workshop hopes to join these threads of the general and the specific, the diachronic and synchronic, and to create a space in which what Lorraine Daston called the “hidden affinities” between disciplines becomes perceptible. Stanford’s Institute for Human-Centered AI, the Stanford Data Science Institute, its leading Digital Humanities center, CESTA, uniquely position the Critical Data Practices workshop to foster cross-disciplinary conversations on these critical issues.