James Evans

How should we incorporate algorithms into humanistic scholarship? The typical approach is to clone what humans have done but faster, extrapolating expert insights to landfills of source material. But creative scholars do not clone tradition; instead, they produce readings that challenge closely held understandings. We theorize and then illustrate how to construct bad robots trained to surprise and provoke. These robots aren’t the most human but rather the most alien—not tame but dangerous. We explore the relationship between the reproduction of tradition and the generation of surprise and then show how formalizing a particular humanistic theory as a Bayesian prior allows us to identify readings that disrupt it through a process of algorithmic abduction. Among the exploding universe of surprising (and mostly ridiculous) possible readings, algorithmic efficiency allows us to select readings that nonetheless garner substantial support from the total archive and so merit interpretation and engagement. It is in such interaction between alien and human readers that meaning is made and understanding disturbed; it is by extending alien readings to novel texts that the scholarly community tests the value of those readings.

Introducing this issue’s triptych on algorithms and culture, this article argues that prevailing modes of analysis that focus on the prospects for algorithms “taking over” are no longer useful. It advocates the need for a new conceptual vocabulary, which recognizes that algorithmic and cultural reasoning processes are already enmeshed with each other. The introduction suggests a need for an enterprise of algorithmic epistemology attuned to the fine structure of the ways in which culture and code have interacted in the past and continue to interact today.