Computational literary studies and AI

Abstract

Although all literary scholars working today are likely to use ‘Artificial Intelligence’ (AI) in their research, it is computational literary studies (CLS) scholars who have most explicitly engaged with large datasets and machine learning algorithms. The most prominent approaches to CLS, distant reading and computational modelling, tend to operate in a discovery mode that conceives of its tools as representing literary objects and cultures. Here we ask how CLS can incorporate insights from the emerging field of critical AI studies, and the work of Wendy Hui Kyong Chun and Louise Amoore in particular, to enact performative inquiries that recognise our epistemological, ontological, and ethico-political entanglement with AI systems. With reference to examples from literary studies and adjacent fields of digital humanities and media studies, we suggest how this performative mode enables literary arguments that are responsive to and responsible with emerging textual formations.