The Core Problem
Question: How does a never-forgetting system recognize sincere behavioral change versus strategic gaming?
Without this, probationary systems are just "amnesty with extra steps." With it, you can implement mercy without corrupting justice. This is the difference between redemption and manipulation.
Humans can barely detect genuine repentance in each other. How do we teach machines?
What Repentance Is NOT
Not Apologies
Words are cheap. Anyone can say "I'm sorry." Apologies are unverifiable intent statements. Gameable: Trivially.
Not Time Elapsed
Waiting doesn't prove change. Time is neutral. You can wait and remain unchanged. Gameable: Just wait out the clock.
Not Completion of Punishment
Serving a sentence doesn't mean you've learned. Punishment does not equal transformation. Gameable: Endure consequences, return to old behavior.
Not Self-Reporting
"I've changed" is unverifiable. Humans lie to themselves and others. Gameable: Extremely.
What Repentance Might Be
Drawing from Alma 42, psychology, behavioral economics, and control theory:
1. Behavioral Convergence Toward Truth
Measurable movement from error state toward correct state, sustained over time.
repentance_signal = (
current_behavior_alignment - past_behavior_alignment
) * consistency_coefficient * time_sustained
Signals: Consistency across contexts. Generalization beyond the specific violation. Voluntary compliance even when unmonitored.
Example in credit scoring: Not just "paid on time for 6 months" but "paid early, reduced debt, engaged with financial literacy resources voluntarily."
2. Sacrifice of Prior Advantage
Willingly giving up benefits gained from the violation. True repentance isn't just "I won't do it again" but "I shouldn't have benefited from it."
sacrifice_coefficient = (
benefits_from_violation - benefits_returned_or_rejected
) / benefits_from_violation
// Closer to 1.0 = genuine repentance signal
Example: Voluntarily deleting a viral misinformation post even if it gained 10k followers.
3. Engagement with Corrective Process
Not passively waiting, but actively working to understand why the violation was wrong and what the correct path looks like.
Signals: Depth of engagement. Questions asked. Application of what was learned in future interactions.
4. Remorse Behavior Patterns
Genuine remorse indicators: acknowledgment without deflection, focus on harm caused (not consequences to self), voluntary repair attempts, changed behavior in related domains.
Strategic regret indicators: minimization, deflection, focus on personal consequences, repetition in other areas.
The Temporal Component
Probationary time is not just delay—it's the period during which change can be demonstrated.
Time windows must be: finite but sufficient, observable, and progressive.
Proposed Formula
repentance_score = (
behavioral_convergence * 0.4 +
sacrifice_coefficient * 0.3 +
engagement_depth * 0.2 +
remorse_authenticity * 0.1
) * (time_sustained / minimum_probation_time)
// Threshold for mercy: repentance_score > 0.75
Note: These weights are completely made up. Need empirical testing.
The Hardest Problem: Gaming
Any metric can be gamed if the reward is high enough. The paradox: if gaming is too easy, justice is corrupted. If gaming is impossible, mercy becomes impossible too.
Potential Solutions
A. Make Gaming Expensive — If genuine repentance signals require sustained effort, sacrifice, and consistency, the cost of faking becomes comparable to actually changing.
B. Multi-Modal Detection — Gaming one signal is possible; gaming all simultaneously is exponentially harder.
C. Transparency + Appeals — Let users see their score. If wrong, they can appeal with evidence.
D. The Mediator Layer — Alma 42's innovation: You don't need a perfect metric if you have a Mediator that absorbs the uncertainty.
Case Study: Credit Scoring
Current state: Missed payments lower your score. No probation. Just time decay. Historical data persists 7+ years.
Algodai implementation:
- Probationary period: 12-24 months calibrated to severity
- Repentance signals: consistent payments, debt reduction, financial literacy engagement, voluntary counseling
- Mediator mechanism: score > 0.75 after 18 months = full restoration
- Justice preserved: violations still happened. But trajectory now matters more than history.
Open Research Questions
- How do you weight the repentance signals? Does it vary by violation type?
- What's the right probation length?
- Can remorse be detected algorithmically without sophisticated NLP?
- How do you handle ambiguous cases (score = 0.60)?
- Can this be done without surveillance?
This is incomplete. We need help.
Behavioral psychologists. ML researchers. Ethicists. Economists. Theologians. Real-world pilots.
If you think this whole approach is fundamentally flawed, we especially need your input.
Join the mailing list to get involved.