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Cited by 29Literary and Philosophical StudiesArtificial Intelligence in GamesArt, Technology, and Culture

Viewpoint: AI as Author – Bridging the Gap Between Machine Learning and Literary Theory

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Van Heerden, Imke, Bas, Anil·2021·Journal of Artificial Intelligence Research
DOI 10.1613/jair.1.12593
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Abstract

Anticipating the rise in Artificial Intelligence’s ability to produce original works of literature, this study suggests that literariness, or that which constitutes a text as literary, is understudied in relation to text generation. From a computational perspective, literature is particularly challenging because it typically employs figurative and ambiguous language. Literary expertise would be beneficial to understanding how meaning and emotion are conveyed in this art form but is often overlooked. We propose placing experts from two dissimilar disciplines – machine learning and literary studies – in conversation to improve the quality of AI writing. Concentrating on evaluation as a vital stage in the text generation process, the study demonstrates that benefit could be derived from literary theoretical perspectives. This knowledge would improve algorithm design and enable a deeper understanding of how AI learns and generates. This article appears in the special track on AI and Society.

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  • Prior work has argued for involving subject matter experts, literary scholars, and industry professionals in developing machine learning models.

    “Previous work has argued for engagement with subject matter experts, literary scholars, and industry professionals in the development of machine learning models [112].”

    From Co-Writing Screenplays and Theatre Scripts with Language Models: Evaluation by Industry Professionals (2023) · cites this paper as [112]

    The Introduction explicitly argues for involving literary scholars in developing machine-learning models, supporting engagement with those subject-matter experts. Section 5 discusses how scholars and professionals might respond to changes in the literary industry, but does not argue that industry professionals should participate in model development. Page numbers are unavailable in our copy. (LLM, conf=0.88)

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Authors
Van Heerden, I., & Bas, A.
Affiliations
Marmara University (TR)
ORCID
Venue
Journal of Artificial Intelligence Research
Publisher
AI Access Foundation
Published
2021-06-06
Volume
71
Pages
175-189
ISSN
1076-9757 (ISSN-L)
DOI
10.1613/jair.1.12593
OpenAlex
W3169190236
Cited by
29
References
94
Citations by year
2026: 4 · 2025: 12 · 2024: 6 · 2023: 3 · 2022: 3 · 2021: 1
FWCI
10.80
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Artificial Intelligence Research (publishedVersion, cc-by)
  • Bournemouth University Research Online (Bournemouth University) (acceptedVersion)
  • Dspace Repository (Marmara Üniversitesi) (submittedVersion)
  • Digital Collections portal (Koç University) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion, other-oa)
Topics
  • Social Sciences › Political Science and International Relations › Literary and Philosophical Studies
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
  • Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
Keywords
AI-generated literature, machine learning, literary theory, literariness, text generation, interdisciplinary collaboration, figurative language, ambiguity, algorithm design

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