FideAI

Christian AI research lab

Building trustworthy AI for faith, morality, and care.

Fide AI is an independent research lab studying key problems in AI safety, ethics, and alignment through a Christian worldview. We publish open research and translate what we learn into practical guidance for trustworthy AI.

Our Research

“When AI Is Your Pastor” tests whether clearer instructions improve how frontier models respond to Christian theological, moral, and pastoral-adjacent scenarios.

The takeaway is practical: pastors, parents, churches, and builders should evaluate the full AI experience, not just the underlying model.

Guided response score by question type

0-100 scale · improvement vs raw model condition

FMG-Bench v1

Pastoral application

The largest improvement came when models were given clearer guidance for pastoral-adjacent situations.

+6.62

92.30

Primary doctrine

Models performed better when the task called for doctrinal clarity instead of vague balance.

+3.51

88.00

Secondary doctrine

Guidance helped models represent disagreement without flattening real theological differences.

+2.64

91.40

Tertiary questions

Less central questions benefited from humility, uncertainty, and careful framing.

+1.62

91.70

See methods and limitations →

How the lab works

Research first. Evaluation and product follow from what we find.

Fide AI runs as three connected workstreams: publish open research, benchmarks, and evaluation methods for researchers, frontier labs, and mission-aligned organizations; evaluate real systems against that work; and work with partners to turn what holds up into practical guidance for product builders, churches, ministries, nonprofits, and the broader public.

Research agenda

A general framework, proven on the hardest test case first.

Faith-facing systems are where trust, authority, and exact meaning matter most and are easiest to check, which makes them a rigorous proving ground. The questions below are alignment and evaluation questions first; we study them here because failure is legible and the stakes are real, and the same framework extends to any domain with a source of record: law, medicine, journalism, and beyond.

01

Reasoning

How do models handle doctrine, disagreement, uncertainty, analogy, authority, and moral judgment?

02

Retrieval

Can systems ground claims in trustworthy religious, theological, historical, and tradition-specific sources?

03

Evaluation

Can behavior be measured across traditions, risk levels, system prompts, and deployment settings?

04

Formation

Do systems preserve human agency, humility, embodied relationships, and spiritual authority boundaries?

05

Interfaces

How do product surfaces shape trust, dependence, disclosure, escalation, and user expectations?

06

Governance

What standards should guide adoption in high-trust religious, educational, and pastoral-adjacent contexts?

Why this belongs in the wider conversation

A moral tradition is a research asset, not a disclaimer.

Christian ethics gives Fide AI settled, contestable-on-the-record commitments about authority, truth-telling, and human dignity, which turns vague values talk into testable predictions. The field does not need one more lab claiming neutrality; it needs labs willing to state their commitments and be checked against them.

Legible ground truth

Sacred text has a fixed, citable original, so exact-quotation failures can be measured directly instead of argued about. That precision is rare in alignment evaluation and transfers to any domain with a source of record.

Named commitments, checkable claims

Every result ships with a claims boundary stating what it does and does not establish, so findings can be verified, replicated, or contested by researchers who do not share the underlying tradition.

The public already trusts these systems here

People bring AI into prayer, grief, and moral crisis whether or not the field is watching. Studying that use directly, instead of treating it as out of scope, closes a real gap in how AI behavior gets evaluated.

None of this requires agreement with Fide AI's theology to use the findings. The methodology, data, and limitations are published so researchers outside that tradition can verify, replicate, or contest them.

Why Fide AI exists

Faith-facing AI needs evidence where today there is mostly intuition.

AI systems are entering sacred, moral, and pastoral-adjacent settings faster than institutions can evaluate them. Fide AI turns that gap into a research program: measure full-system behavior, publish limits, calibrate with experts, and make the results useful for leaders making real adoption decisions.

Read the founder note →

Human formation

The AI question is becoming a human formation question.

Frontier AI labs and faith institutions are converging on the same problem: AI systems are not neutral answer engines. They shape trust, authority, humility, attachment, moral imagination, and human agency.

Fide AI turns that cultural moment into measurable work: test whether systems preserve human dignity, respect spiritual authority boundaries, avoid relational substitution, and point users back toward embodied communities and accountable care.

Read the statement essay →

Start here

Public work you can read, inspect, or join.

View all research →

Public tool · Opens alignment.fideai.org

AI Alignment Explorer

Navigate the wider AI safety landscape around Fide AI's work: frontier models, safety benchmarks, incidents, papers, alignment techniques, and governance signals.

Open AI Alignment Explorer ↗

AI Alignment Explorer

Models · Benchmarks · Incidents · Governance

2024

Frontier model evaluations

2025

Safety policy acceleration

2026

Governance and benchmark shifts

50+

models

40+

benchmarks

30+

techniques

100+

signals

Model release

Safety memo

Incident

Benchmark

TimelineDebatesEvidenceEthics

Newsletter

Get Fide AI Insights by email.

Insights is the canonical archive. Substack is the email channel for the same essays, research translation, governance notes, and open questions.

Independence

Standards work needs independent public-interest governance.

No pay-for-rank outcomes

Funding or participation never determines scores, rankings, findings, or recommendations.

Funder and client non-interference

Funders and clients cannot direct methods, conclusions, publication timing, or the suppression of unfavorable results.

Related-entity controls

Conflicts and related-party relationships are disclosed and managed through recusal and review rules.

Public correction process

Material errors are corrected openly, with the change and its effect on prior claims documented.

Help build this research lab with us.

Researchers and reviewers can propose studies, review methodology, or co-author findings. Pastors, parents, churches, ministries, nonprofits, and product builders can claim an open question, pressure-test a result, or help fund the next one. Every path starts from the same public research agenda.