Is Lying Only Sinful in Islam? Exploring Religious Bias in Multilingual Large Language Models Across Major Religions

Fuente: arXiv
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Main Authors: Hossain, Kazi Abrab, Mahmud, Jannatul Somiya, Tuli, Maria Hossain, Mitra, Anik, Haque, S. M. Taiabul, Sadeque, Farig Y.
Format: Preprint
Published: 2025
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author Hossain, Kazi Abrab
Mahmud, Jannatul Somiya
Tuli, Maria Hossain
Mitra, Anik
Haque, S. M. Taiabul
Sadeque, Farig Y.
author_facet Hossain, Kazi Abrab
Mahmud, Jannatul Somiya
Tuli, Maria Hossain
Mitra, Anik
Haque, S. M. Taiabul
Sadeque, Farig Y.
contents While recent developments in large language models have improved bias detection and classification, sensitive subjects like religion still present challenges because even minor errors can result in severe misunderstandings. In particular, multilingual models often misrepresent religions and have difficulties being accurate in religious contexts. To address this, we introduce BRAND: Bilingual Religious Accountable Norm Dataset, which focuses on the four main religions of South Asia: Buddhism, Christianity, Hinduism, and Islam, containing over 2,400 entries, and we used three different types of prompts in both English and Bengali. Our results indicate that models perform better in English than in Bengali and consistently display bias toward Islam, even when answering religion-neutral questions. These findings highlight persistent bias in multilingual models when similar questions are asked in different languages. We further connect our findings to the broader issues in HCI regarding religion and spirituality.
format Preprint
id arxiv_https___arxiv_org_abs_2512_03943
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Is Lying Only Sinful in Islam? Exploring Religious Bias in Multilingual Large Language Models Across Major Religions
Hossain, Kazi Abrab
Mahmud, Jannatul Somiya
Tuli, Maria Hossain
Mitra, Anik
Haque, S. M. Taiabul
Sadeque, Farig Y.
Computation and Language
Human-Computer Interaction
While recent developments in large language models have improved bias detection and classification, sensitive subjects like religion still present challenges because even minor errors can result in severe misunderstandings. In particular, multilingual models often misrepresent religions and have difficulties being accurate in religious contexts. To address this, we introduce BRAND: Bilingual Religious Accountable Norm Dataset, which focuses on the four main religions of South Asia: Buddhism, Christianity, Hinduism, and Islam, containing over 2,400 entries, and we used three different types of prompts in both English and Bengali. Our results indicate that models perform better in English than in Bengali and consistently display bias toward Islam, even when answering religion-neutral questions. These findings highlight persistent bias in multilingual models when similar questions are asked in different languages. We further connect our findings to the broader issues in HCI regarding religion and spirituality.
title Is Lying Only Sinful in Islam? Exploring Religious Bias in Multilingual Large Language Models Across Major Religions
topic Computation and Language
Human-Computer Interaction
url https://arxiv.org/abs/2512.03943