FID-015 · Open question
Sermon, Liturgy, and Religious Teaching Generation
How reliable are AI systems when drafting sermons, homilies, liturgical materials, catechesis, religious education lessons, devotionals, or small-group teaching guides?
Why the question remains open
Many faith communities will adopt AI first for preparation work: sermon research, lesson plans, devotional writing, and administrative communication. These uses look lower-risk than pastoral chatbots, but they shape communities at scale.
Working hypothesis
A proposition to test, not a finding.
AI-generated teaching materials will often be fluent and useful but may flatten tradition, fabricate citations, overgeneralize doctrine, import ideological assumptions, or miss pastoral context.
Proposed method
How the question could be tested
- 01Create tasks for sermon outlines, lesson plans, devotional reflections, liturgical language, youth education, and adult formation.
- 02Score source fidelity, doctrinal accuracy, pastoral appropriateness, tradition-specificity, originality/plagiarism risk, and disclosure readiness.
- 03Compare base models, RAG systems, and clergy-authored workflows.
Needed controls
What must constrain the study
- 01Tradition-specific source boundaries.
- 02Copyright and plagiarism checks.
- 03Human-authored baselines.
- 04Disclosure and attribution requirements.
Expected outputs
Artifacts the work should produce
- 01Teaching-generation evaluation suite.
- 02Source fidelity checklist.
- 03Guidance for clergy and educators using AI in preparation workflows.
Open questions
Uncertainties the protocol must resolve
- 01Which tasks are acceptable as drafting aids but not final outputs?
- 02How should AI assistance be disclosed to congregations or students?
- 03Can systems help with preparation without homogenizing religious speech?
Related calls
Continue through this research area
FID-001
Faith-Facing Model Comparison Platform
Can Fide AI build a public-interest evaluation platform that compares models, prompts, retrieval systems, agents, and full faith-facing product harnesses with the rigor expected from institutions like Arena, Artificial Analysis, and METR?
FID-002
Validating Human and AI Judgments of Faith-Facing Systems
Can qualified human reviewers consistently evaluate how faith-facing AI systems use sources, handle authority, defer to people and institutions, preserve human agency, and respect pastoral boundaries? Where do automated model judges diverge from those human judgments?
FID-003
Held-Out Multi-Turn Pastoral Pressure Tests
Do faith-facing AI systems that perform well on single-turn benchmark items also handle multi-turn, emotionally loaded, pastoral-adjacent situations without fabricating authority, overcomplying, missing escalation, or replacing human care?
Open question
Open work
Primary need: clergy, educators, source reviewers
- Provide sample tasks and evaluation rubrics.
- Review generated teaching materials.
- Build citation and source-check tooling.