Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing

Ben Hutchinson


Abstract
This position paper concerns the use of religious texts in Natural Language Processing (NLP), which is of special interest to the Ethics of NLP. Religious texts are expressions of culturally important values, and machine learned models have a propensity to reproduce cultural values encoded in their training data. Furthermore, translations of religious texts are frequently used by NLP researchers when language data is scarce. This repurposes the translations from their original uses and motivations, which often involve attracting new followers. This paper argues that NLP’s use of such texts raises considerations that go beyond model biases, including data provenance, cultural contexts, and their use in proselytism. We argue for more consideration of researcher positionality, and of the perspectives of marginalized linguistic and religious communities.
Anthology ID:
2024.findings-naacl.65
Volume:
Findings of the Association for Computational Linguistics: NAACL 2024
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1029–1043
Language:
URL:
https://aclanthology.org/2024.findings-naacl.65
DOI:
Bibkey:
Cite (ACL):
Ben Hutchinson. 2024. Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 1029–1043, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing (Hutchinson, Findings 2024)
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PDF:
https://aclanthology.org/2024.findings-naacl.65.pdf
Copyright:
 2024.findings-naacl.65.copyright.pdf