Henrickson, L orcid.org/0000-0001-8008-2373 and Meroño Peñuela, A (2022) The Hermeneutics of Computer-Generated Texts. Configurations, 30 (2). pp. 115-139. ISSN 1080-6520
Abstract
As cultural circumstances become increasingly digital, the importance of theoretical frameworks guiding calculated considerations of authorial intention and reader response is being reaffirmed. The framework proposed in this article is that of hermeneutics: the study of understanding, of processes of meaning-making. Although explicit application of hermeneutics has fallen out of fashion, the field is especially valuable for critically approaching digital texts. This article thus serves as a reintroduction to hermeneutics, particularly for digital textual study. It offers an overview of historical hermeneutical views, and then applies a hermeneutics perspective to a new kind of text made possible by digital technologies: computer-generated prose. Through analysis and repurposing of OpenAI's GPT-2 software, this paper argues that the reintegration of hermeneutics in digital textual studies may contribute to more comprehensive understandings of both human and computer intention, especially in instances of computer-generated texts. Digital technologies are changing conventional understandings of authorship and reader responsibility; hermeneutics helps us understand what these changes are, how they have come to be, and why they matter.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Johns Hopkins University Press and the Society for Literature, Science, and the Arts. This is an author produced version of an article published in Configurations. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | hermeneutics, computer-generated texts, digital literature, reader response, GPT-2 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Arts, Humanities and Cultures (Leeds) > School of Media & Communication (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Jan 2022 14:58 |
Last Modified: | 17 Mar 2023 01:45 |
Status: | Published |
Publisher: | Johns Hopkins University Press |
Identification Number: | 10.1353/con.2022.0008 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182902 |