Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing
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Abstract (arXiv)
Artificial intelligence (AI) alignment is fundamentally a formation problem, not only a safety problem. As Large Language Models (LLMs) increasingly mediate moral deliberation and spiritual inquiry, they do more than provide information; they function as instruments of digital catechesis, actively shaping and ordering human understanding, decision-making, and moral reflection. To make this formative influence visible and measurable, we introduce the Flourishing AI Benchmark: Christian Single-Turn (FAI-C-ST), a framework designed to evaluate Frontier Model responses against a Christian understanding of human flourishing across seven dimensions. By comparing 20 Frontier Models against both pluralistic and Christian-specific criteria, we show that current AI systems are not worldview-neutral. Instead, they default to a Procedural Secularism that lacks the grounding necessary to sustain theological coherence, resulting in a systematic performance decline of approximately 17 points across all dimensions of flourishing. Most critically, there is a 31-point decline in the Faith and Spirituality dimension. These findings suggest that the performance gap in values alignment is not a technical limitation, but arises from training objectives that prioritize broad acceptability and safety over deep, internally coherent moral or theological reasoning.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 26 references that are in the map. First posted on arXiv 3 Apr 2026.
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4 of 26 references.
References · 4
- 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
- 2024A Survey on LLM-as-a-Judgecited by 1,384
- 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,023
- 2023Eight Things to Know about Large Language Modelscited by 73
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Citing papers per year: 2026: 1.
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- 2025The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis
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