MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

AI-generated literature and the vectorized Word

Author(s)
Heflin, Judy(Judy Ann)
Thumbnail
Download1193319920-MIT.pdf (6.442Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Comparative Media Studies.
Advisor
Nick Montfort.
Terms of use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
This thesis focuses on contemporary AI-generated literature that has been traditionally published in the form of a printed book, labeled and interpreted as something written by "artificial intelligence," and that necessarily depends on vector representations of linguistic data. This thesis argues that AI-generated literature is not a monolithic practice that erases the role of the author, but rather encompasses a diversity of practice that includes divergent artistic and writerly perspectives. Through an in-depth look at three books of contemporary AI-generated literature and discussions with their human authors, this thesis details the authorial and writerly labor throughout the stages of datafication, vectorization, generation, and pagination in order to categorize the writerly practices that are involved in the creation of this type of work. This thesis also considers how these practices are preceded by "analog" types of writing, compares divergent authorial perspectives, and discusses ways of reading AI-generated literature, including a material analysis of how AI-generated text interacts with the printed book, how authors and publishers use paratextual elements to guide readings, along with additional points of entry for analyzing literary AI-generated texts.
Description
Thesis: S.M. in Comparative Media Studies, Massachusetts Institute of Technology, Department of Comparative Media Studies/Writing, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 139-146).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/127563
Publisher
Massachusetts Institute of Technology
Keywords
Comparative Media Studies.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.