On a near-daily basis, data is being used to narrate our lives. Categorizing algorithms drawn from amassed personal data to assign narrative destinies to individuals at crucial junctures, simultaneously predicting and shaping the paths of our lives. Data is commonly assumed to bring us closer to objectivity, but the narrative paths these algorithms assign seem, more often than not, to replicate biases about who an individual is and could become.

While the social effects of such algorithmic logics seem new and newly urgent to consider, Collecting Lives looks to the late nineteenth and early twentieth century U.S. to provide an instructive prehistory to the underlying question of the relationship between data, life, and narrative. Rodrigues contextualizes the application of data collection to human selfhood in order to uncover a modernist aesthetic of data that offers an alternative to the algorithmic logic pervading our sense of data’s revelatory potential. Examining the work of W. E. B. Du Bois, Henry Adams, Gertrude Stein, and Ida B. Wells-Barnett, Rodrigues asks how each of these authors draw from their work in sociology, history, psychology, and journalism to formulate a critical data aesthetic as they attempt to answer questions of identity around race, gender, and nation both in their research and their life writing. These data-driven modernists not only tell different life stories with data, they tell life stories differently because of data.

Elizabeth Rodrigues is Assistant Professor and Humanities and Digital Scholarship Librarian at Grinnell College.

— Jasmine Rault, University of Toronto

— Wesley Beal, Lyon College