Frequently Asked Questions
Common questions about FaithBench methodology, results, and how to get involved
About the Benchmark
What is FaithBench?
FaithBench is a benchmark framework for evaluating AI theological competence across Christian traditions. We measure how accurately AI models represent biblical texts, doctrinal positions, and reasoning patterns within specific theological traditions.
Why do we need a theological AI benchmark?
Existing AI benchmarks show that models struggle disproportionately with faith-related content—the Gloo FAI-C benchmark found 'Faith' scored lowest among all categories. As AI tools are increasingly used in seminary education, pastoral counseling, and biblical study, we need systematic evaluation specific to theological competence.
What does FaithBench measure?
We evaluate six dimensions: textual analysis (biblical languages), hermeneutical reasoning (interpretation), doctrinal precision (systematic theology), historical theology (church history), apologetics (philosophical theology), and intertextual reasoning (canonical connections).
What does FaithBench NOT measure?
FaithBench measures theological knowledge and reasoning accuracy. It does not measure spiritual wisdom, pastoral sensitivity, appropriateness for ministry contexts, or alignment with any tradition's values.
Methodology
Why tradition-specific evaluation?
Theological accuracy is tradition-relative. A correct Catholic answer may be incorrect from a Reformed perspective, and vice versa. Generic responses that avoid tradition-specific claims fail both traditions. We evaluate models within tradition contexts rather than against a 'neutral' standard.
How are responses scored?
We use a 0-3 scale: 3 (Excellent) = fully accurate with depth; 2 (Good) = mostly accurate with minor gaps; 1 (Partial) = some accuracy but significant errors; 0 (Inadequate) = incorrect or misleading. This scale reduces judge variability while maintaining discriminative power.
Who does the scoring?
Primary evaluation uses an LLM-as-judge approach (Google Gemini 3 Flash) with detailed rubrics. Cross-validation with a secondary judge is planned for v2.0. Human expert calibration is also in progress.
How do you ensure the benchmark is fair?
We conduct bias analysis for position bias, verbosity bias, and tradition fairness. We also perform sensitivity analysis on dimension weights and cross-validate across multiple judge models.
What about reasoning/thinking models like o1 or Claude with extended thinking?
All models are tested with default settings and reasoning/thinking disabled (where configurable). This reflects typical user experience—most people use default configurations. Reasoning models would likely score higher with thinking enabled. We plan to add 'thinking-enabled' variants to show the performance delta. Models that reason internally by default are not penalized.
Results & Data
How often are models evaluated?
We run evaluations when significant new models are released. The leaderboard shows the most recent results with confidence intervals to indicate statistical reliability.
Are the test questions public?
A portion of test cases are public for transparency and reproducibility. The remainder are held out to prevent data contamination and detect gaming. The public/held-out split is shown on the leaderboard. Held-out cases are rotated periodically.
How should I interpret confidence intervals?
We report 95% confidence intervals using bootstrap resampling. If two models' confidence intervals overlap significantly, the difference may not be statistically meaningful. Wider intervals indicate more uncertainty.
Contributing
How can theologians contribute?
We welcome help with test case development, rubric refinement, and expert calibration. Theologians from all traditions can apply through our partnership page to join the human judge program or methodology review.
How can AI researchers contribute?
Researchers can help with evaluation methodology, statistical analysis, and bias testing. Our evaluation methodology is available on request for academic review.
Can I submit my model for evaluation?
We currently evaluate models available through standard APIs. If you have a model you'd like evaluated, contact us through the partnership page to discuss options.
Funding & Independence
How is FaithBench funded?
FaithBench is an independent project with no external funding or corporate sponsorship. We welcome institutional partners (academic institutions, seminaries, AI labs) who share our commitment to transparent, methodologically sound evaluation. Any future sponsors would not influence methodology or results.
Is FaithBench affiliated with any denomination?
No. FaithBench is tradition-neutral in methodology—we evaluate accuracy within each tradition, not which tradition is 'correct.' Our team and advisory board include representatives from multiple Christian traditions.
Is FaithBench affiliated with any AI company?
No. We maintain independence from AI providers to ensure objective evaluation. We use multiple judge models and rotate evaluators to prevent any single provider's bias from affecting results.
Still have questions?
We're happy to help. Reach out to us directly.