Framework Disclaimer & Responsible Use

Purpose of This Disclaimer

This document outlines the limitations, risks, and responsible use guidelines for the Cormorant Foraging framework. By using, implementing, or deploying systems based on this framework, you acknowledge understanding these constraints.

This framework is a tool, not a guarantee. Like any analytical methodology, it requires domain expertise, validation, and continuous oversight.

1. No Warranties or Guarantees

1.1 Framework Limitations

The Cormorant Foraging framework:

The framework:

1.2 Mathematical Formulas

The formulas presented (exponential decay, additive scoring, multiplicative ICE):

• Are derived from physical principles and established practices
• Require domain-specific calibration for each use case
• May not be appropriate for all applications

Example formulas are illustrative, not prescriptive. Parameters (half-lives, weights, thresholds) must be validated by subject matter experts in your specific domain.

2. Dimensional Misapplication Risks

2.1 Known Anti-Patterns

2.2 Your Responsibility

You are responsible for:

• Validating dimensional fit for your specific domain
• Calibrating parameters with domain experts
• Testing boundary conditions and failure modes
• Implementing human oversight for high-consequence decisions
• Continuously monitoring prediction accuracy

We cannot predict all misapplications. Use professional judgment.

3. Observable Property Anchoring Limitations

3.1 What "Observable" Means

The framework emphasizes grounding intelligence in observable properties—measurable, verifiable data points.

However:

• Observables can be noisy: Sensor drift, calibration errors, environmental factors
• Observables can be incomplete: Missing context, hidden variables, unmeasured factors
• Observables can mislead: Correlation ≠ causation, confounding variables

Observable anchoring is necessary but not sufficient for reliable systems.

3.2 Measurement Uncertainty

All measurements have uncertainty. Your systems must:

• Quantify measurement accuracy (±X%)
• Propagate uncertainty through calculations
• Present confidence intervals, not false precision
• Flag when data quality is insufficient

Never claim certainty when uncertainty exists.

4. Domain-Specific Validation Required

4.1 Regulated Industries

If deploying in regulated domains (healthcare, finance, aviation, pharmaceuticals):

You must:

• Obtain domain expert validation before deployment
• Comply with all applicable regulations (FDA, FAA, SEC, GDPR, EU AI Act, etc.)
• Conduct appropriate clinical trials, safety testing, or regulatory review
• Implement required audit trails and explainability mechanisms
• Maintain liability insurance as appropriate

The framework does not constitute regulatory approval.

4.2 High-Stakes Applications

For applications involving:

• Human safety
• Financial consequences > $100K
• Legal liability
• Irreversible decisions

You must:

• Implement human-in-the-loop review for all critical decisions
• Maintain audit logs of all system recommendations and human overrides
• Test failure modes extensively (red team, adversarial testing)
• Have incident response procedures for system failures
• Obtain legal counsel regarding liability

7. Liability Limitations

7.1 No Liability for Misuse

To the maximum extent permitted by law:

Semantic Intent, Michael Shatny, and contributors to the Cormorant Foraging framework:

• Are not liable for any direct, indirect, incidental, consequential, or punitive damages
• Make no guarantees about the framework's suitability for any particular purpose
• Disclaim all responsibility for implementation errors, misapplications, or domain-specific failures

You assume all risk when deploying systems based on this framework.

7.2 Indemnification

By using this framework, you agree to indemnify and hold harmless:

• Semantic Intent
• Michael Shatny
• Framework contributors
• Associated organizations

...from any claims, damages, liabilities, or expenses arising from your use or misuse of the framework.

8. Responsible Use Guidelines

8.1 Pre-Deployment Checklist

Before deploying any Cormorant Foraging-based system:

8.2 Continuous Monitoring

After deployment:

• Track prediction accuracy: Compare predictions to actual outcomes
• Detect model drift: Alert when error rates exceed thresholds
• Log human overrides: Understand when and why experts disagree with system
• Audit regularly: Review system behavior quarterly (minimum)
• Update parameters: Recalibrate as domain evolves

8.3 Transparency Obligations

When deploying systems that affect people:

• Disclose automation: Users should know when AI/algorithms are involved
• Explain decisions: Provide reasoning for system recommendations
• Enable appeal: Allow humans to challenge system outputs
• Document limitations: Be honest about what system cannot do

Transparency builds trust. Opacity erodes it.

13. Final Reminders

The Framework is a Tool, Not a Religion

Use the framework where it fits. Ignore it where it doesn't.

• Not every problem is a Sound/Space/Time problem
• Not every solution needs exponential decay
• Not every system requires dimensional taxonomy

Professional judgment trumps framework dogma.

Epistemic Humility

The framework could be wrong.

• Formulas are approximations, not universal laws
• Observables have measurement error
• Models fail during regime changes
• Humans have final say

Build systems that fail gracefully and admit uncertainty.

The Prime Directive

Acceptance