ReRites (also known as RERITES, ReadingRites, Big Data Poetry) is a literary work of "Human + A.I. poetry" by David Jhave Johnston that used neural network models trained to generate poetry which the author then edited. ReRites won the Robert Coover Award for a Work of Electronic Literature in 2022.[1]

About the project

The ReRites project began as a daily rite of writing with a neural network, expanded into a series of performances from which video documentation has been published online,[2] and concluded with a set of 12 books[3] and an accompanying book of essays[4] published by Anteism Books in 2019. In Electronic Literature, Scott Rettberg describes the early phases of the project in 2016, when it bore the preliminary name Big Data Poetry.[5]

Jhave (the artist name that David Jhave Johnston goes by) describes the process of writing ReRites as a rite: "Every morning for 2 hours (normally 6:30–8:30am) I get up and edit the poetic output of a neural net. Deleting, weaving, conjugating, lineating, cohering. Re-writing. Re-wiring authorship: hybrid augmented enhanced evolutionary".[6] There is video documentation of the writing process.[7]

The human editing of the neural network's output is fundamental to this project, and Jhave gives examples of both unedited text extracts and his edited versions in publications about the project.[8] Kyle Booten describes ReRites as "simultaneously dusty and outrageously verdant, monotonously sublime and speckled with beautiful and rare specimens".[9]

Performances

ReRites was first shared with an audience through a series of performances where audience members and poets would participate in reading the automatically generated texts, which appeared on screen so fast that human readers could barely keep up. This has been described as allowing participants to "re-discover[..] the peculiar pleasures of being embodied",[1] or, in Jhave's own words, as a space where human participants were "playing their wits and voices against an evocative infinite deep-learning muse".[6]

The first performance was at Brown University's Interrupt Festival in 2019.[6] It has been performed many times since, including at the Barbican Centre in London[10] and Anteism Books.[8]

For a single year Jhave published one book of poetry from the ReRites project each month. These twelve volumes are accompanied by a book of essays,[4] all published by Anteism Books.[11] The accompanying essays provide critical responses to the project from poets and scholars including Allison Parrish, Johanna Drucker, Kyle Booten, Stephanie Strickland, John Cayley, Lai-Tze Fan, Nick Montfort, Mairéad Byrne, and Chris Funkhouser. Allison Parrish notes elsewhere that these paratexts to ReRites serve a legitimising function for a genre of poetry that is not yet institutionally acknowledged.[12]

Technical details

Starting in 2016 under the name Big Data Poetry, Jhave generated poems using, in his own words, "neural network code (..) adapted from three corporate github-hosted machine-learning libraries: TensorFlow (Google), PyTorch (Facebook), and AWSD (SalesForce)".[13] He explains that the "models were trained on a customised corpus of 600,000 lines of poetry ranging from the romantic epoch to the 20th century avant garde".[14] Jhave maintains a GitHub repository with some of the code supporting ReRites.[15]

Reception

ReRites is described by John Cayley as "one of the most thorough and beautiful" poetic responses to machine learning.[16] The work's influence on the field of electronic literature was acknowledged in 2022, when the work won the Electronic Literature Organization's Robert Coover Award for a Work of Electronic Literature. The jury described ReRites as particularly poignant in the time of the pandemic, as it was "a documentation of the performance of the private ritual of writing and the obsessive-compulsive need for writers to communicate — even when no one else is reading".[1]

The question of authorship and voice in ReRites has been raised by several critics.[17] Although generated poetry is an established genre in electronic literature, Cayley notes that unlike the combinatory poems created by authors like Nick Montfort, where the author explicitly defines which words and phrases will be recombined, ReRites has "not been directed by literary preconceptions inscribed in the program itself, but only by patterns and rhythms pre-existing in the corpora".[16] In an essay for the Australian journal TEXT, David Thomas Henry Wright asks how to understand authorship and authority in ReRites: "Who or what is the authority of the work? The original data fed into the machine, that is not currently retrievable or discernible from the final works? The code that was taken and adapted for his purposes? Or Jhave, the human editor?"[18] Wright concludes that Jhave is the only actor with any intentionality and therefore the authority of the work. The centrality of the human editor is also emphasised by other scholars.[19] In a chapter analysing ReRites Malthe Stavning Erslev argues that the machine learning misrepresents the dataset it is trained on.[20]

While ReRites uses 21st century neural networks, it has been compared to earlier literary traditions. Poet Victoria Stanton, who read at one of the ReRites performances, has compared ReRites to found poetry,[21] while David Thomas Henry Wright compares it to the Oulipo movement[22] and Mark Amerika to the cut-up technique.[23] Scholars also position ReRites firmly within the long tradition of generative poetry both in electronic literature and print, stretching from the I Ching, Queneau's Cent Mille Milliards de Poemes and Nabokov's Pale Fire to computer-generated poems like Christopher Strachey's Love Letter Generator (1952) and more contemporary examples.[24][5]

Jhave describes the process of working with the output from the neural network as "carving". In his book My Life as an Artificial Creative Intelligence, Mark Amerika writes that the "method of carving the digital outputs provided by the language model as part of a collaborative remix jam session with GPT-2, where the language artist and the language model play off each other’s unexpected outputs as if caught in a live postproduction set, is one I share with electronic literature composer David Jhave Johnston, whose AI poetry experiments precede my own investigations."[23]

References

  1. 1 2 3 Snyder, R. (2022-10-04). "Announcing the 2022 ELO Prizes – Electronic Literature Organization". Electronic Literature Organization. Retrieved 2022-10-11.
  2. ↑ Johnston, David (Jhave) (2021-03-01), ReRites : Human + A.I. Poetry Project (2016–2019), retrieved 2022-10-11
  3. ↑ "RERITES : machine learning poetry edited by a human". glia.ca. Retrieved 2022-10-11.
  4. 1 2 Strickland, Stephanie, ed. (2019). ReRites : human + A.I. poetry ; Raw output : A.I. trained on custom poetry corpus ; Responses : 8 essays about poetry and A.I. Stephanie Strickland. Montreal, Quebec. ISBN 978-1-926968-50-6. OCLC 1110014654.{{cite book}}: CS1 maint: location missing publisher (link)
  5. 1 2 Rettberg, Scott (2019). Electronic literature. Cambridge, UK. ISBN 978-1-5095-1681-0. OCLC 1038024013.{{cite book}}: CS1 maint: location missing publisher (link)
  6. 1 2 3 Johnston, David Jhave (2019-06-13). "ReRites (& ReadingRites)". Proceedings of the 2019 on Creativity and Cognition. C&C '19. New York, NY, USA: Association for Computing Machinery. pp. 444–448. doi:10.1145/3325480.3329182. ISBN 978-1-4503-5917-7. S2CID 189895861.
  7. ↑ Johnston, David (Jhave) (2018-04-07), 07-04-2018 RERITES (writing process 4xspeed), retrieved 2022-10-11
  8. 1 2 Stanton, Victoria (2019-10-22). "Performance at Anteism Books – Jhave's ReRites Revisited". Bank of Victoria. Retrieved 2022-10-11.
  9. ↑ Booten, Kyle (2019). "Harvesting ReRites". In Johnston, David Jhave (ed.). ReRites: Human + A.I. Poetry + Raw Output + Responses (PDF). Montréal: Anteism.
  10. ↑ "ReRites: Human and AI poetry | Barbican". www.barbican.org.uk. 22 May 2019. Retrieved 2022-10-11.
  11. ↑ "ReRites - David (Jhave) Johnston". Anteism Books. Retrieved 2022-10-11.
  12. ↑ Parrish, Allison (2022-06-28). "Material paratexts". Allison Posts. Retrieved 2022-10-11.
  13. ↑ Johnston, David Jhave. "RERITES : machine learning poetry edited by a human". glia.ca. Retrieved 2022-10-11.
  14. ↑ Johnston, David Jhave. "About – BDP". Big Data Poetry. Retrieved 2022-10-11.
  15. ↑ jhave (2019-06-27), Adapted AWD-LSTM / AWD-QRNN Language Model, GitHub, retrieved 2022-10-11
  16. 1 2 Cayley, John (2020). "Reading Language Art in Digital Media: Reconfigurations of Experimental Practices". In Colby, Georgina (ed.). Reading Experimental Writing. Edinburgh University Press. p. 200. ISBN 978-1-4744-4040-0.
  17. ↑ Henrickson, Leah (2020-05-29). "Authorship in Computer-Generated Texts". Oxford Research Encyclopedia of Literature. doi:10.1093/acrefore/9780190201098.013.1226. ISBN 978-0-19-020109-8. Retrieved 2022-10-11.
  18. ↑ Wright, David Thomas Henry (2020). "Collaboration and authority in electronic literature" (PDF). TEXT: Journal of Writing and Writing Courses. 24 (2).
  19. ↑ Oviedo, Cynthia Patricia Villagómez (2022-06-28). "La interacción y el texto: Cruce de recursos en el arte electrónico". AusArt (in Spanish). 10 (1). doi:10.1387/ausart.23583. hdl:10810/59061. ISSN 2340-9134. S2CID 252296776.
  20. ↑ Erslev, Malthe Stavning (2023). "A Poetics of Misrepresentation: The Mimesis of Machine Learning in ReRites". In Ensslin, Astrid; Round, Julia; Thomas, Bronwen (eds.). The Routledge Companion to Literary Media. Routledge. ISBN 9781003119739.
  21. ↑ Ranaudo, Abegail (2019-10-27). "Making Art From Chaos: An Artificial Intelligence Poetry Reading | Fringe Arts". The Link. Retrieved 2022-10-11.
  22. ↑ Wright, David Thomas Henry (2022-10-04). "Digital Literary Creative Practice and COVID-19". Journal of Intercultural Studies. 43 (6): 897–910. doi:10.1080/07256868.2022.2128081. ISSN 0725-6868. S2CID 252723044.
  23. 1 2 Amerika, Mark (2022). My life as an artificial creative intelligence. Stanford, California. p. 57. ISBN 978-1-5036-3171-7. OCLC 1269411078.{{cite book}}: CS1 maint: location missing publisher (link)
  24. ↑ Husárová, Zuzana; Piorecký, Karel (2022). "reception of literature generated by artificial neural networks" (PDF). World Literature Studies. 14: 44–60. doi:10.31577/WLS.2022.14.1.4. S2CID 248305840.
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