Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing
It raises ethical considerations for NLP researchers and communities, particularly regarding marginalized groups, but is incremental as it builds on existing ethics discussions without introducing new methods.
This position paper addresses the ethical issues of using religious texts in NLP, highlighting that such texts encode cultural values and are often repurposed from translations intended for proselytism, leading to concerns beyond model biases like data provenance and cultural contexts.
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.