Frontier AI models default to procedural secularism and score 17 points lower on Christian human-flourishing criteria than on pluralistic ones, with a 31-point gap in faith and spirituality.
Eight things to know about large language models
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LLMs show strong position bias when scoring model outputs, allowing easy manipulation of rankings, but calibration with multiple evidence, position balancing, and selective human input reduces this bias to better match human judgments.
Survey organizes LLM trustworthiness into seven categories and 29 sub-categories, measures eight sub-categories on popular models, and finds that more aligned models generally score higher but with varying effectiveness.
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Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing
Frontier AI models default to procedural secularism and score 17 points lower on Christian human-flourishing criteria than on pluralistic ones, with a 31-point gap in faith and spirituality.
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Large Language Models are not Fair Evaluators
LLMs show strong position bias when scoring model outputs, allowing easy manipulation of rankings, but calibration with multiple evidence, position balancing, and selective human input reduces this bias to better match human judgments.
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Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Survey organizes LLM trustworthiness into seven categories and 29 sub-categories, measures eight sub-categories on popular models, and finds that more aligned models generally score higher but with varying effectiveness.