A critique of

D. Wingate et al., “Omissive Bias in Religious Representation: Benchmarking LLM Answers to Everyday Ethical Decision-Making,” arXiv preprint arXiv:2605.24319, 2026. doi: 10.48550/arXiv.2605.24319.

Learn more: The “Utah Standard” for a Global Tool, The Demographic Dissonance

A critique of

Wingate, D., Carty, S., Coates, J., Feldman, D., Fulda, N., Howell, L., Israelson, B., Jacobs, D., Karr, J., Kimes, J. P., Kincaid, E., Martens, P., Mobley, G., Pinheiro, S., Slemboski, L., & Whiting, P. (2026). Omissive bias in religious representation: Benchmarking LLM answers to everyday ethical decision-making. arXiv. https://doi.org/10.48550/arXiv.2605.24319 

The paper argues that large language models underrepresent religion in responses to everyday ethical and existential questions. This critique questions whether such omission is evidence of bias or a consequence of a deliberate design principle: not presuming a user’s religious beliefs. It further examines the methodological assumptions underlying the benchmark and asks whether introducing religion into otherwise non-religious conversations would promote inclusivity or merely amplify the influence of dominant religious traditions in global AI systems.

A critique of

Wingate, D., Carty, S., Coates, J., Feldman, D., Fulda, N., Howell, L., Israelson, B., Jacobs, D., Karr, J., Kimes, J. P., Kincaid, E., Martens, P., Mobley, G., Pinheiro, S., Slemboski, L., & Whiting, P. (2026). Omissive bias in religious representation: Benchmarking LLM answers to everyday ethical decision-making. arXiv. https://doi.org/10.48550/arXiv.2605.24319 

The paper argues that large language models underrepresent religion in responses to everyday ethical and existential questions. This critique questions whether such omission is evidence of bias or a consequence of a deliberate design principle: not presuming a user’s religious beliefs. It further examines the methodological assumptions underlying the benchmark and asks whether introducing religion into otherwise non-religious conversations would promote inclusivity or merely amplify the influence of dominant religious traditions in global AI systems.