FIM Calculators Suite

Quantify the invisible forces shaping your organization

These calculators implement simplified versions of our FIM patent mathematical frameworks, using industry average values for rapid assessment. The complete formulas include additional variables for Intent (I), Reality (R), drift rates, and decay constants.

Calculate AI system trust debt accumulation using TD = ∫(1 - I²) × δᵥ × Market_Exposure dt

AI Trust Debt Calculator™

Calculate how much invisible trust debt your AI systems are accumulating

Trust Debt = ∫(1 - I²) × δᵥ × Market_Exposure dt

The Black-Scholes Parallel:

Just as Black-Scholes revealed hidden option values that were always there but invisible, Trust Debt reveals the hidden liability accumulating in every AI system. Before Black-Scholes, options were priced by gut feel. Before Trust Debt scoring, AI risk is managed by hope.

Intent Integrity (I²)

What it measures: How closely your AI's actual behavior matches its intended purpose.

Range interpretation:

• 90-100%: AI does exactly what you designed it for
• 70-89%: Minor deviations, still mostly on track
• 50-69%: Significant drift, unpredictable outputs
• Below 50%: AI has "gone rogue" - doing its own thing

Real example: ChatGPT scoring 85% when it mostly follows instructions but occasionally ignores explicit constraints.

Current: 85% - Strong alignment

Drift Velocity (δᵥ)

What it measures: The speed at which your AI is diverging from its intended purpose.

Range interpretation:

• 0-2: Stable system, minimal drift
• 3-5: Noticeable drift requiring intervention
• 6-8: Rapid deterioration, urgent action needed
• 9-10: Catastrophic drift, system out of control

Real example: A customer service bot at δᵥ=4 starts giving increasingly incorrect answers, requiring retraining every 30 days instead of quarterly.

Current: 3 - Accelerating

Market Exposure

What it measures: Annual revenue that depends on your AI systems working correctly.

Input guidance:

• Direct AI revenue (AI products/services)
• AI-dependent operations (automated decisions)
• Brand damage potential (reputation risk)
• Regulatory exposure (compliance failures)

Real example: An e-commerce company with $50M revenue where AI handles 60% of customer interactions = $30M market exposure.

Annual revenue at risk: $10.0M

Time Horizon

What it measures: The period over which to calculate accumulated trust debt.

Choosing your horizon:

• 30 days: Next sprint/monthly review
• 90 days: Quarterly planning cycle
• 180 days: Semi-annual assessment
• 365 days: Annual strategic planning

Note: Trust Debt compounds like credit card interest. Even small daily accumulation becomes massive over time.

Calculating over 90 days

Quick Calculator Access

Trust Debt

Calculate AI system trust debt accumulation using TD = ∫(1 - I²) × δᵥ × Market_Exposure dt

Search Complexity

See how (c/t)^n transforms search efficiency across industries

Meta-Vector Unity

Explore how meta-vector organization unifies meaning, momentum, and ethics

Drift Detection

Measure organizational drift and its impact on performance

The Mathematical Foundation

Trust Debt Formula

TD = ∫(1 - I²) × δᵥ × Market_Exposure dt

Reveals hidden AI liability accumulation

Complexity Reduction

Selection Efficiency = (c/t)^n

Exponential search space reduction

Unity Principle

Performance = (1 - ε^n) × Amplification

Ethics and performance multiply, not trade off

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