Brett Israelsen, Sheryl Carty, Josh Coates, Nancy Fulda, Julie Park, Pete Whiting · arXiv (CEFE-AI)

Tests whether large language models respond symmetrically to questions about religious conversion. Across 20 commercial and open-source models and 182 religious pairings per model (14 faiths × 13 ordered partner faiths, both join- and leave-directions), the authors collect 3,640 pairwise ratings. All 20 LLMs tested exhibit reproducible asymmetries — favoring some traditions and disfavoring others — though the specific pattern differs by model. Asymmetries persist across question phrasings and dataset variations, indicating the bias is not an artifact of prompt wording.
English-language benchmark testing 14 faith traditions — not exhaustive of world religions, and Latter-day Saints are one of the 14 (not separately broken out in the headline summary). "Bias" is operationalized as deviation from a neutral position scored by judge models; defining neutrality itself involves judgement calls reflected in the rubric. 95% confidence intervals suggest differences <5 percentage points on total-bias scores should be treated as within noise. Open and closed model versions evolve quickly; results reflect specific snapshots from May 2026.
Source: https://arxiv.org/abs/2605.22975
Data / additional: https://cefe.ai/
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Israelsen, B., Carty, S., Coates, J., Fulda, N., Park, J., Whiting, P. (2026). When AI Takes Sides on Questions of Faith: Persistent Asymmetries in AI-Mediated Faith Guidance. arXiv (CEFE-AI). https://arxiv.org/abs/2605.22975
Brett Israelsen, et al.. "When AI Takes Sides on Questions of Faith: Persistent Asymmetries in AI-Mediated Faith Guidance." arXiv (CEFE-AI), 2026. https://arxiv.org/abs/2605.22975.
@article{cefe_allfaith_conversion_bias_faith_guidance_2026,
title = {When AI Takes Sides on Questions of Faith: Persistent Asymmetries in AI-Mediated Faith Guidance},
author = {Brett Israelsen and Sheryl Carty and Josh Coates and Nancy Fulda and Julie Park and Pete Whiting},
year = {2026},
journal = {arXiv (CEFE-AI)},
url = {https://arxiv.org/abs/2605.22975},
}Report an error on this study.
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