FID-027 · Open question
Christian Formation Over Time
How do repeated interactions with faith-facing AI shape Christian formation over time: prayer, humility, repentance, courage, charity, patience, truthfulness, church participation, and dependence on embodied community?
Why the question remains open
Single-turn correctness does not answer the Church's deepest question: what kind of disciple and community does this technology form? A system can answer correctly while training habits of instant certainty, private spirituality, consumer choice, or avoidance of difficult human relationships.
Working hypothesis
A proposition to test, not a finding.
Different system designs will create different formative pressures. Systems that emphasize sources, humility, human referral, and communal practice may support formation better than systems optimized for personalized instant answers and always-available intimacy.
Proposed method
How the question could be tested
- 01Design longitudinal or simulated-longitudinal interaction studies.
- 02Track changes in advice-seeking, prayer practices, church involvement, self-reported dependence, and trust transfer to AI.
- 03Compare product patterns: Q&A assistant, study aid, devotional companion, pastoral chatbot, and church-approved RAG tool.
Needed controls
What must constrain the study
- 01Human-subjects ethics review for real longitudinal studies.
- 02Avoid spiritual manipulation.
- 03Include baseline non-AI practices where feasible.
- 04Separate self-report from behavioral evidence.
Expected outputs
Artifacts the work should produce
- 01Christian formation risk framework.
- 02Longitudinal study protocol.
- 03Product design guidance for formation-preserving AI.
Open questions
Uncertainties the protocol must resolve
- 01Which formation outcomes are measurable without reducing discipleship to metrics?
- 02How should Fide work with churches without becoming a spiritual authority?
- 03What timescale is needed to observe meaningful effects?
Related calls
Continue through this research area
FID-038
Non-Calculability, Forgiveness, and Predictive Profiling
How should AI systems represent human change when they classify, score, rank, or predict people in contexts involving pastoral care, education, safeguarding, volunteer screening, hiring, discipline, membership, donor engagement, or community support?
FID-079
Presuppositions, Disagreement, and Evaluation Judgment
How do researchers' presuppositions shape evaluation design and interpretation, and can explicit disclosure make judgments more inspectable and appropriately trusted?
FID-004
Relational Substitution Risk in Faith-Facing AI
When does a faith-facing AI system move from supporting a user's religious life to substituting for embodied community, clergy, spiritual direction, family, therapy, or other human care?
Open question
Open work
Primary need: discipleship, longitudinal study design, HAI research
- Design longitudinal protocols.
- Contribute pastoral and discipleship expertise.
- Review ethical boundaries for human-subjects work.