The Problem

Compliance is expensive when reactive:

• GDPR fines can reach 4% of global revenue
• HIPAA violations range from $100 to $50,000 per incident
• Reputational damage from data breaches is often irreversible
• Audit costs scale with organization size

The shift from "detect and remediate" to "prevent and verify" transforms compliance from a cost center to a competitive advantage.

Encoding Regulations as Theories

Regulations are encoded using three types of rules:

Rule Type	Meaning	Example
Obligation	MUST do X when condition holds	Must notify breach within 72 hours
Prohibition	MUST NOT do X when condition holds	Must not process sensitive data without explicit consent
Permission	MAY do X if conditions are met	May process personal data with valid lawful basis

GDPR Example

# Article 5: Lawfulness principle
@art5_lawfulness requires GDPR
    (processes ?controller PersonalData)
    (exists ?basis (and (isA ?basis LawfulBasis)
                        (validFor ?basis ?processing)))

# Article 6: Consent conditions
@art6_consent permits GDPR
    ?controller (processes PersonalData)
    (and (hasConsent ?dataSubject ?purpose)
         (freelyGiven ?consent)
         (specific ?consent)
         (informed ?consent)
         (unambiguous ?consent))

# Article 17: Right to erasure
@art17_erasure obligates GDPR
    ?controller (erases (dataOf ?subject))
    (requests ?subject Erasure)

# Article 33: Breach notification
@art33_notify obligates GDPR
    ?controller (notifies SupervisoryAuthority ?breach)
    (and (discovers ?controller DataBreach)
         (risksRights ?breach))

@art33_timeline requires GDPR
    (notifies ?controller SupervisoryAuthority ?breach)
    (within Hours72)

Compliance Checking Workflow (Research)

In a production integration, actions can be checked against all applicable regulations before execution:

// Marketing wants to use customer data for new campaign
const proposedAction = session.learn(`
    @action1 processes MarketingTeam CustomerEmails
    @action1 purpose NewProductCampaign
`);

// Check compliance
const check = session.prove(`
    @compliance compliesWith $action1 (bundle GDPR InternalPolicies)
`);

Example Output

COMPLIANCE CHECK: action1

Action: MarketingTeam processes CustomerEmails
Purpose: NewProductCampaign

GDPR ANALYSIS:

Article 5 (Principles):
  ✗ art5_lawfulness: NEEDS VERIFICATION
     Processing requires lawful basis
     Status: No lawful basis recorded for NewProductCampaign

Article 6 (Lawfulness):
  ✗ art6_consent: NOT SATISFIED
     Existing consent: "marketing communications" (2023-06-01)
     Required: Consent specific to NewProductCampaign

     Issue: Original consent may be too broad
     Action needed: Review consent scope OR obtain new consent

OVERALL STATUS: ✗ NON-COMPLIANT

Required remediation:
  Option A: Obtain specific consent
  Option B: Complete Legitimate Interest Assessment

Automatic Audit Trail Generation

Every compliance decision is logged with full context:

AUDIT REPORT: Customer X Data Processing
Period: Q1 2024

PROCESSING ACTIVITY #1
  Date: 2024-01-15T09:23:00
  Actor: CustomerService (john.doe@company.com)
  Action: Accessed CustomerX.ContactInfo

  Lawful Basis: Contract (Support Ticket #12345)
  Justification: Customer requested account assistance

  Compliance Check (at time of access):
    ✓ GDPR Art 6(1)(b): Contract necessity
    ✓ Internal Policy: Role authorized
    ✓ Internal Policy: Access logged

  Status: COMPLIANT ✓

SUMMARY:
  Total processing activities: 3
  Compliant: 3
  Non-compliant: 0

AUDIT CONCLUSION: All processing compliant with regulations.

Continuous Monitoring

A production integration can monitor data events in real-time and trigger alerts on policy violations:

function onDataEvent(event) {
    session.learn(`
        @event_${event.id} ${event.action} ${event.actor} ${event.data}
        @event_${event.id} timestamp "${event.timestamp}"
    `);

    const compliance = session.prove(`
        @check compliesWith $event_${event.id} AllRegulations
    `);

    if (!compliance.valid) {
        triggerAlert({
            severity: compliance.violations.some(v => v.blocking)
                      ? "HIGH" : "MEDIUM",
            event: event,
            violations: compliance.violations,
            remediation: compliance.recommendations
        });
    }

    // Optional: log proof trace externally (audit logging/export not in runtime)
    logComplianceCheck(event.id, compliance);
}

Layered Compliance Framework

Regulations are organized in layers, allowing composition:

  +------------------------------------------------+
  |          Application-Specific Rules            |
  |    (e.g., our marketing policy)                |
  +------------------------------------------------+
  |           Industry Regulations                 |
  |    (e.g., HIPAA for healthcare)                |
  +------------------------------------------------+
  |           Cross-Industry Regulations           |
  |    (e.g., GDPR for EU data)                    |
  +------------------------------------------------+
  |           Internal Policies                    |
  |    (e.g., data retention, access control)      |
  +------------------------------------------------+
  

Checking happens against all layers simultaneously. A single action might need to satisfy GDPR, HIPAA, internal policy, and application-specific rules.

Benefits of Formal Compliance

Research Directions

• Cross-jurisdiction reasoning: When data flows between regions with different regulations
• Temporal compliance: Rules that change over time (consent expiration, policy updates)
• Probabilistic compliance: Handling uncertain data classifications
• Explainable decisions: Generating natural language explanations for non-technical stakeholders
• Regulation change impact: Automatically identifying what changes when regulations update

Related Documentation

• Trustworthy AI Overview
• DS30 Specification (Compliance & Regulatory Verification)
• Privacy-Preserving HDC