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?
Why this matters
The question behind the brief.
Predictive systems can identify people with past behavior, inferred traits, productivity, donor value, risk categories, or reputational labels. Christian accounts of repentance, forgiveness, conversion, vocation, accountability, and restoration resist reducing a person to a score or past pattern. Faith-facing AI needs ways to preserve both prudence and the possibility of real change.
Metadata
How to place this idea.
Ways to help
Move this from question to evidence.
Draft scenarios involving discipline, safeguarding, education, hiring, and pastoral care.
Review rubrics for mercy, accountability, due process, and contestability.
Connect this work to algorithmic fairness and risk-assessment research.
Help design safeguards for sensitive institutional pilots.
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