What does it mean when we say that computers can ‘write’ and how are recent developments in neural networks and machine learning changing this capacity? This article examines the long-standing literary fear of authorship being replaced by machines while also interrogating the labour and credit implications that sit behind widely used structures of authorship in a technological age. The argument makes reference to one work of computer-generated writing – Johannes Heldén & Håkan Jonson’s Evolution [2014] – and to one software paradigm (a character-based recurrent neural networks for language acquisition trained on the corpus of the journal Textual Practice). I here argue that unless we conceive more broadly of the criteria for ‘authorship’ as a labour function, and unless we take seriously the need to see textual production as social production, hybridized (but predominantly) machine identities will come to dominate a literary landscape.