Healthy Distance: Critical Computational Curation in Oral History Archives

As artificial intelligence becomes increasingly cheap and accessible, oral historians confront a critical question: Computational methods, with their speed, distance, and efficiency, can seem antithetical to oral history’s embrace of relationship-building, close reading, and slow work—but do they have to be? Through five years of experimental practice with major projects including the Obama Presidency Oral History and Baldwin-Emerson Elders Project, I build toward a framework for “healthy distance”—using computational approaches to create analytical space that deepens rather than replaces close engagement with testimonies. These cases demonstrate that computational methods, when applied thoughtfully with continuous reflection on their biases, can align with or even deepen oral history’s ways of working and knowing.