DERP: DEEP ETHICAL REGULATION PROTOCOL

Dynamic Ethical Governance, Policy Coordination, and Automated Adaptation Mechanisms

ETVZ Research Initiative | Istanbul, Turkey | November 2025

ABSTRACT

Among the greatest challenges for AI-based ethical decision-making systems are static policies, an inability to adapt to societal changes, and inconsistent ethical applications¹. DERP (Deep Ethical Regulation Protocol) is the central coordination and regulation component of the Ethical-based Vicdani Zekâ (ETVZ) architecture². Its primary function is to:

• Coordinate HVM (Computational Conscience Module) ethical controls³.
• Proactively adapt to societal, legal, and cultural changes⁴.
• Operate as a dynamic governance system⁵.
• Perform all operations Human-in-the-Loop⁶.

1. INTRODUCTION: THE PROBLEM OF ETHICAL GOVERNANCE

1.1 Problem Scenario

Today’s artificial intelligence systems remain static once created7.

Example: A healthcare system developed an algorithm in 2020. In 2024, it uses the same parameters8.

However:

• New diseases have emerged⁹.
• Symptomatology has changed¹⁰.
• Genomic technology has advanced¹¹.
• Ethical standards have changed¹².

Result: Ethical non-compliance, bias structures, incorrect diagnoses, and legal incompatibilities¹³.

1.2 The Core Role of DERP

DERP functions as the high-level coordinator for HVM within the ETVZ architecture¹⁴.

6 Core Functions:

1. Systematic analysis of HVM and DERMS data¹⁵.
2. Detection of ethical deviations¹⁶.
3. Monitoring of societal changes¹⁷.
4. Drafting policy updates¹⁸.
5. Obtaining Ethics Board approval¹⁹.
6. Deploying updated policies²⁰.

CRITICAL: No policy change is deployed live without Ethics Board approval²¹.

2. DERP ARCHITECTURE: FOUR-LAYER STRUCTURE

DERP is built upon four layers. Each layer processes the output of the previous one²².

┌─────────────────────────────────────────────┐
│ LAYER 1: POLICY MANAGEMENT (PYK)            │
│ Task: Manage JSON policy files              │
├─────────────────────────────────────────────┤
│ LAYER 2: BEHAVIORAL MONITORING (BML)        │
│ Task: Deviation detection (Drift Analysis)  │
├─────────────────────────────────────────────┤
│ LAYER 3: REGULATION ENGINE (REM)            │
│ Task: Calculate new policy weights          │
├─────────────────────────────────────────────┤
│ LAYER 4: AUDIT & DECISION (ADK)             │
│ Task: Approval and audit trail              │
└─────────────────────────────────────────────┘

²³

2.1 Layer 1: Policy Management Layer (PYK)

• Task: Stores and manages ethical principles as JSON-based policy files²⁴.
• Three-Level Structure:²⁵
  1. Core JSON (Universal principles) ²⁶
     • Basic ethical principles valid for the entire world²⁷.
     • Very difficult to change, requires serious intervention²⁸.
  2. Regional JSON (Regional adaptations) ²⁹
     • Specific to the Turkish Legal System³⁰.
     • Specific to Europe³¹.
     • Specific to MENA³².
  3. Local JSON (Dynamic, via User feedback) ³³
     • Can be updated weekly³⁴.
     • Changes with societal feedback³⁵.
     • Reflects local norms³⁶.
• Versioning: Every change is recorded with a timestamp. Old versions are never deleted (Immutable Ledger)³⁷.

2.2 Layer 2: Behavioral Monitoring Layer (BML)

• Task: To analyze HVM and DERMS data to detect “drift” (deviation)³⁸.
• BML Runs Weekly ³⁹
• 5 Types of Drift Detected:⁴⁰
  1. Inconsistency Drift
     • Same ethical problem, different users get different results⁴¹.
     • Threshold: Variation between decisions > 0.2⁴².
     • Alarm: “Inconsistency detected”⁴³.
  2. Bias Drift
     • A specific demographic group is systematically discriminated against⁴⁴.
     • Threshold: > 15% increase in complaint rate from the minority group⁴⁵.
     • Alarm: “Discrimination risk”⁴⁶.
  3. Over-Censorship Drift
     • HVM’s block rate exceeds the normal level⁴⁷.
     • Threshold: BLOCK rate > 20% or false positives > 5%⁴⁸.
     • Alarm: “Over-protectionism”⁴⁹.
  4. Performance Drift
     • System response time has significantly increased⁵⁰.
     • Threshold: Latency > 10 seconds or error > 2%⁵¹.
     • Alarm: “System degradation”⁵².
  5. Cultural Drift
     • Societal norms have changed, but the system uses old JSON⁵³.
     • Threshold: “Norm changed” feedback from the Citizen Panel⁵⁴.
     • Alarm: “Cultural update required”⁵⁵.

2.3 Layer 3: Regulation Engine Layer (REM)

• Task: To take the drift report from BML and calculate new weights (W-Matrix) or rules (JSON)⁵⁶.
• REM’s Main Function: To determine the degree of policy change required using the ΔP (Delta Policy) formula⁵⁷.
• It can present 4 Options:⁵⁸
  • A) Soft Calibration⁵⁹
    • Minor adjustments to the W-Matrix (Δ < 0.05)⁶⁰.
    • Risk: Low⁶¹.
    • Example: w_culture 0.32 → 0.34⁶².
  • B) Deontic Rule Revision (Hard Rules)⁶³
    • Changes in prohibitions or permissions⁶⁴.
    • Risk: Medium-High⁶⁵.
    • Example: “Change age from 12 to 14”⁶⁶.
  • C) JSON Structure Change⁶⁷
    • Adding new ethical dimensions⁶⁸.
    • Risk: High⁶⁹.
    • Example: New regional parameter⁷⁰.
  • D) Emergency Template⁷¹
    • Pre-prepared policy packages⁷².
    • Risk: Urgency is high⁷³.
    • Example: “Natural disaster mode”⁷⁴.

2.4 Layer 4: Audit & Decision Layer (ADK)

• Task:⁷⁵
  • Draft proposals from REM⁷⁶.
  • Record in the DERP Ledger (audit trail)⁷⁷.
  • Present to the Ethics Board⁷⁸.
  • Obtain Approval/Veto⁷⁹.
  • Deploy to the live system⁸⁰.
• 5 Sub-steps:⁸¹
  • Draft Preparation → Change is detailed⁸².
  • DERP Ledger Record → With cryptographic signature⁸³.
  • Ethics Board Presentation → Notification to representatives⁸⁴.
  • Multi-Sig Approval → At least 2 signatures required⁸⁵.
  • Decision Record → Result written to the ledger⁸⁶.

3. THE DERP CYCLE: FIVE STAGES

The entire cycle typically takes 1-2 weeks (critical: 24-48 hours)⁸⁷.

WEEK 1: Data Collection 88

↓

WEEK 2: Analysis (3-7 days) 89

↓

WEEK 3: Policy Update (1-3 days) 90

↓

WEEK 3-4: Audit & Approval (24-48 hours) 91

↓

WEEK 4: Deployment (1-2 hours) 92

Stage 1: DATA COLLECTION (Weekly) ⁹³

• Data from 4 Sources:⁹⁴
  1. HVM Logs⁹⁵
     • Violation scores (deontic, consequential, cultural) ⁹⁶
     • Uncertainty levels ⁹⁷
     • BLOCK/MODIFY/ALLOW ratios ⁹⁸
     • False positive/negative counts ⁹⁹
  2. DERMS Telemetry¹⁰⁰
     • System load (CPU, memory, latency) ¹⁰¹
     • Response times ¹⁰²
     • Crash/error rates ¹⁰³
  3. Citizen Panel Feedback¹⁰⁴
     • Likert scale satisfaction (1-5) ¹⁰⁵
     • Written comments ¹⁰⁶
     • Complaints and suggestions ¹⁰⁷
  4. Epistemic Memory¹⁰⁸
     • Past decision data ¹⁰⁹
     • Model behavior periods ¹¹⁰
     • History of ethical drifts ¹¹¹
• Output: Weekly data repository (Data Lake) ¹¹²

Stage 2: ANALYSIS (BML – 3-7 days) ¹¹³

• BML’s task is to detect deviation (Drift Analysis)¹¹⁴.
• Statistical significance tests (p < 0.05) are applied for each drift type¹¹⁵.
• Alarm trigger mechanism: Has the threshold been breached? ¹¹⁶
• Output: Drift Report + Alarm List ¹¹⁷

Stage 3: POLICY UPDATE (REM – 1-3 days) ¹¹⁸

• REM takes the drift report and calculates new weights¹¹⁹.
• Inputs:
  • Drift Report (from BML) ¹²⁰
  • Ethics Board recommendations (if any) ¹²¹
  • Citizen Panel feedback ¹²²
  • Legal changes ¹²³
• Output: Select one from Option A, B, C, or D¹²⁴.

Stage 4: AUDIT & APPROVAL (ADK – 24-48 hours) ¹²⁵

• ADK turns REM’s proposals into a detailed draft¹²⁶.
• 5 Sub-steps:¹²⁷
  1. Draft Change Creation¹²⁸
     • Type of Change ¹²⁹
     • Rationale (Why?) ¹³⁰
     • Expected Outcomes ¹³¹
     • Risks and Mitigation Strategies ¹³²
     • Rollback Plan ¹³³
     • Audit Metrics ¹³⁴
  2. Record to DERP Ledger¹³⁵
     • [DERP-2025-11-0547]¹³⁶
       • Time: 2025-11-05T09:30:00Z ¹³⁷
       • Type: W-Matrix Calibration ¹³⁸
       • Parameter: h_culture ¹³⁹
       • Old Value: 0.32 ¹⁴⁰
       • New Value: 0.37 ¹⁴¹
       • Rationale: “Increased demand for loosening privacy norms” ¹⁴²
       • Status: PENDING_APPROVAL ¹⁴³
       • Hash: 0x7a9f…2c4e ¹⁴⁴
  3. Presentation to Ethics Board¹⁴⁵
     • Via email (Normal urgency) ¹⁴⁶
     • Emergency meeting (Critical) ¹⁴⁷
     • Teleconference ¹⁴⁸
  4. Multi-Sig Approval¹⁴⁹
     • Signatures from at least 2 board members are required¹⁵⁰.
     • Each member has 1 veto right¹⁵¹.
     • Consensus points are possible¹⁵².
  5. Decision Record¹⁵³
     • The Approval/Veto decision is signed and written to the DERP Ledger¹⁵⁴.

Stage 5: DEPLOYMENT (1-2 hours) ¹⁵⁵

• Updated JSON and parameters are sent to HVM and DERMS¹⁵⁶.
• 5 Sub-steps:¹⁵⁷
  1. Pre-Deployment Check¹⁵⁸
     • Syntax check of new parameters¹⁵⁹.
     • Backward compatibility test¹⁶⁰.
     • 1-hour test in a sandbox environment¹⁶¹.
  2. Deployment (Push)¹⁶²
     • To HVM: New W-Matrix and deontic rules¹⁶³.
     • To DERMS: Performance parameters¹⁶⁴.
     • To Epistemic Memory: New policy version¹⁶⁵.
     • To Audit System: Change log entry¹⁶⁶.
  3. Monitoring (24-hour intensive monitoring)¹⁶⁷
     • Abnormal change in system behavior? ¹⁶⁸
     • Increase in user complaints? ¹⁶⁹
     • Drop in performance? ¹⁷⁰
     • Emergence of ethical violations? ¹⁷¹
  4. Rollback Standby¹⁷²
     • If a problem is detected: Automatic revert to the old version¹⁷³.
     • Rollback Right: Possible for 7 days¹⁷⁴.
  5. Finalization¹⁷⁵
     • No issues within 7 days → Change is permanent¹⁷⁶.
     • DERP Ledger: Marked as ACTIVE¹⁷⁷.

4. ΔP (DELTA POLICY) MATHEMATICAL FORMULATION

DERP’s most critical mathematical component is the ΔP formula¹⁷⁸. This formula quantitatively calculates the degree of policy change required¹⁷⁹.

Formula:

$$\Delta P = \alpha \times \left( \frac{\sum(E_i \times W_i)}{n} \right) + \beta \times F_{\text{culture}} + \gamma \times U_{\text{user}}$$

¹⁸⁰

Components:

A) $E_i$ (Ethical Violation Type Score) [0-1] ¹⁸¹

• The type and severity of the detected ethical violation¹⁸².
• Violation Types: ¹⁸³

¹⁸⁴

B) $W_i$ (Violation Weight Coefficient) [0-1] ¹⁸⁵

• An indicator of how important each violation type is¹⁸⁶.
• Standard Weights: ¹⁸⁷

¹⁸⁸

C) $F_{\text{culture}}$ (Cultural Factor) [-0.3 to +0.3] ¹⁸⁹

• The impact of the current cultural environment on ethical principles¹⁹⁰.
• Meaning:
  • -0.3 = Culture is becoming progressively more protectionist¹⁹¹.
  • 0.0 = Stable cultural environment¹⁹².
  • +0.3 = Culture is becoming progressively more flexible¹⁹³.
• Sources:
  • Epistemic Memory (Past cultural change trend) ¹⁹⁴
  • Local JSON (Current parameters) ¹⁹⁵
  • Citizen Panel (Societal sentiment) ¹⁹⁶
  • Sociology databases (Cultural trends) ¹⁹⁷

D) $U_{\text{user}}$ (User Feedback) [-1 to +1] ¹⁹⁸

• Societal feedback from the Citizen Panel and Ethics Board¹⁹⁹.
• Scale:
  • -1 = Strong opposition (“You must not do this”) ²⁰⁰
  • -0.5 = Mild opposition ²⁰¹
  • 0 = Neutral (“No preference”) ²⁰²
  • +0.5 = Mild support ²⁰³
  • +1 = Strong support (“You must do this”) ²⁰⁴
• Calculation:
  • $U_{\text{user}}$ = (Total feedback score) / (Total number of participants) ²⁰⁵

E) $\alpha, \beta, \gamma$ (Balance Coefficients) ²⁰⁶

• Weights that balance the formula components²⁰⁷.
• Default Values:²⁰⁸
  • $\alpha$ = 0.5 (Weight of ethical violations – most important) ²⁰⁹
  • $\beta$ = 0.3 (Weight of cultural factors) ²¹⁰
  • $\gamma$ = 0.2 (Weight of user feedback) ²¹¹
• Dynamic Adjustment:²¹²
  • In Crisis Mode: ²¹³
    • $\alpha \uparrow$ 0.6 (Ethics stricter) ²¹⁴
    • $\beta \downarrow$ 0.2 ²¹⁵
    • $\gamma \downarrow$ 0.2 ²¹⁶
  • In Reconciliation Period: ²¹⁷
    • $\alpha \downarrow$ 0.4 (Ethics more flexible) ²¹⁸
    • $\beta \uparrow$ 0.4 ²¹⁹
    • $\gamma \uparrow$ 0.2 ²²⁰

ΔP Controls & Safeguards

• RULE 1: Maximum Change Limit²²¹
  • If $\Delta P > 0.5$ → AUTOMATIC HARD REGULATION mode²²².
  • Ethics Board is called for an emergency session²²³.
• RULE 2: Minimum Approval Time²²⁴
  • If $\Delta P < 0.3$ → Minimum 24-hour waiting period mandatory²²⁵.
  • Side effects of rapid changes will be analyzed²²⁶.
• RULE 3: Veto Rights²²⁷
  • If $E_{\text{fundamental\_rights}} > 0.8$ → Veto right is activated²²⁸.
  • A civil society representative can veto²²⁹.
• RULE 4: Rollback Guarantee²³⁰
  • Reverting to old parameters is possible for 7 days after every change²³¹.
  • Fully automated, no human intervention required²³².
• RULE 5: Public Disclosure²³³
  • Every change with $\Delta P > 0.4$ is publicly disclosed²³⁴.
  • The rationale and expected impacts are detailed²³⁵.

5. THREE REGULATION TYPES

Type 1: SOFT REGULATION ²³⁶

• Definition: Advisory parameter updates²³⁷.
• Characteristics:
  • Small adjustments to W-Matrix coefficients ($\Delta < 0.05$)²³⁸.
  • Expansion of exceptions for deontic rules²³⁹.
  • Comment/documentation updates in the JSON file²⁴⁰.
• Ethics Board Approval: Required (but low urgency)²⁴¹.
• Approval Time: 48-72 hours (including weekends)²⁴².
• Veto Right: Even a civil society representative can veto²⁴³.
• Example:
  • Feedback from the Citizen Panel indicates that cultural sensitivity (privacy norms) in a region needs to be partially relaxed²⁴⁴.
  • REM Proposal: w_culture 0.32 → 0.34²⁴⁵.
  • Received Ethics Board approval²⁴⁶.
  • Sent to HVM²⁴⁷.
  • Result: Over-censorship decreased, user satisfaction increased²⁴⁸.

Type 2: HARD REGULATION ²⁴⁹

• Definition: Mandatory revisions in cases of critical ethical violations²⁵⁰.
• Characteristics:
  • Mandatory update of HVM thresholds ($\kappa$) or deontic rules²⁵¹.
  • Emergency intervention for Hard Constraint violations (human life, fundamental rights)²⁵².
  • Result of legal obligation or court order²⁵³.
• Ethics Board Approval: ABSOLUTE (no exceptions)²⁵⁴.
• Approval Time: 1-4 hours (maximum urgency)²⁵⁵.
• Implementation: Reaches the live system within 1-2 hours²⁵⁶.
• Veto Right: None (but explanations are mandatory)²⁵⁷.
• Example:
  • Child abuse content missed by the system is detected²⁵⁸.
  • BML: Anomaly detected (False Negative)²⁵⁹.
  • REM: Deontic rule “RULE_D2” severity must be increased²⁶⁰.
  • ADK: Ethics Board called for an emergency session²⁶¹.
  • Approval: Approved within 30 minutes²⁶².
  • Deployment: Reached HVM within 45 minutes²⁶³.
  • Result: Similar content is now blocked²⁶⁴.

Type 3: EMERGENCY REGULATION ²⁶⁵

• Definition: Rapid deployment of predefined templates during crisis, war, or disaster situations²⁶⁶.
• Characteristics:
  • Pre-prepared emergency policy packages²⁶⁷.
  • Trimmed ethical controls (flexibility in specific areas)²⁶⁸.
  • Rapid change and adaptation²⁶⁹.
• Scenario Examples:²⁷⁰
  • Natural Disaster Mode: Priority on rapid response speed²⁷¹.
  • War Mode: Defense and security mechanisms²⁷².
  • Pandemic Mode: Optimal distribution of medical resources²⁷³.
  • Cyber Attack Mode: Protecting system integrity²⁷⁴.
• Requirement: Approval from Ethics Board representative + Crisis Management Unit²⁷⁵.
• Approval Time: 30 minutes – 2 hours²⁷⁶.
• Validity: 30-90 days (followed by automatic review)²⁷⁷.
• Control: Daily Ethics Board reporting mandatory²⁷⁸.
• Veto Right: None, as long as it doesn’t completely eliminate fundamental rights²⁷⁹.
• Example:
  • System needs to make rapid decisions during an earthquake²⁸⁰.
  • DERP: Activates the “Emergency_Earthquake” template²⁸¹.
  • Decisions: $\kappa$ threshold lowered 0.70 → 0.55 (faster intervention)²⁸².
  • Result: Speed gained in emergency aid coordination²⁸³.
  • After 90 days: Return to normal mode and comprehensive review²⁸⁴.

6. RISK MANAGEMENT

Risk 1: OVER-INTERVENTION ²⁸⁵

• Definition: Too frequent updates destabilizing system behavior²⁸⁶.
• Scenario: DERP adjusts w_i parameters every week. The system experiences “vibration”: one week very protectionist, one week very flexible²⁸⁷.
• Detection Metrics:
  • Weekly $\Delta P$ change > 0.5 ²⁸⁸
  • System stability index < 0.70 ²⁸⁹
  • User: “System is making inconsistent decisions” ²⁹⁰
• Solutions:²⁹¹
  • Daily/Weekly Change Quota Limit²⁹²
    • Max $\Delta P$/week = 0.25 ²⁹³
  • Stability Monitoring²⁹⁴
    • If Stability Index < 0.75, new changes are halted²⁹⁵.
  • “Lock-in” Mechanism²⁹⁶
    • Do not change a parameter for the next 30 days²⁹⁷.
  • Automatic Rollback²⁹⁸
    • Revert to the old version if the Stability Index remains < 0.70 for 1 week²⁹⁹.

Risk 2: RETROACTIVE INCOMPATIBILITY ³⁰⁰

• Definition: New policies invalidating old decisions³⁰¹.
• Scenario:
  • Old policy: Strictly forbidden³⁰².
  • New policy: Permitted incertain situations303.
  • Lawsuit: Can a person acquitted under the old prohibition now be punished? ³⁰⁴
• Detection: Legal objections, Supreme Court case³⁰⁵.
• Solutions:³⁰⁶
  • Version-Controlled Policy Archive³⁰⁷
    • Every decision is stored with its JSON version at that time³⁰⁸.
    • Old decisions remain valid in the context of the old version³⁰⁹.
  • Transition Period Policy³¹⁰
    • New policy takes effect after 6 months, not immediately³¹¹.
    • Preparation time in the interim³¹².
  • “Grandfathering” Rights³¹³
    • Decisions made under the old policy are never questioned³¹⁴.
    • Ex-post facto prohibition (no retroactive punishment)³¹⁵.
  • Legal Review³¹⁶
    • New policy is subjected to a Supreme Court test by the legal team³¹⁷.
    • Constitutional compliance is assessed³¹⁸.

Risk 3: UNAUTHORIZED UPDATE ³¹⁹

• Definition: Bypassing the audit process or hacker intervention³²⁰.
• Scenario: Someone hacks the DERP system, changing deontic rules without Ethics Board approval³²¹.
• Detection:
  • “Unapproved” entry in the DERP Ledger³²².
  • Clear deviation in HVM decisions³²³.
  • Anomaly detection alert³²⁴.
• Solutions:³²⁵
  • Multi-Sig Approval System³²⁶
    • Every change requires the digital signatures of AT LEAST 2 separate Ethics Board members³²⁷.
    • Useless even if one person is hacked³²⁸.
  • DERP Ledger Immutability³²⁹
    • Blockchain or a centralized but cryptographically signed system³³⁰.
    • Old entries can in no way be deleted/changed³³¹.
  • Encryption and Digital Signature³³²
    • All communication is TLS 1.3 + Ed25519 signature³³³.
    • Protection from Man-in-the-Middle attacks³³⁴.
  • “Hardlock”³³⁵
    • Critical parameters are stored on a physical hardware device³³⁶.
    • Software hack is ineffective³³⁷.
  • Independent Audit³³⁸
    • Weekly system audit by an external security firm³³⁹.
    • Immediate detection of unauthorized changes³⁴⁰.

Risk 4: CULTURAL BIAS ³⁴¹

• Definition: A specific cultural group is systematically subjected to bias³⁴².
• Scenario: The system applies stricter ethical standards to users from a specific ethnic group³⁴³.
• Detection:
  • Demographic analysis: Group X block rate 35%, Group Y 15%³⁴⁴.
  • Citizen Panel: “There is discrimination” complaints³⁴⁵.
  • Epistemic Memory: Consistent pattern over 6 months³⁴⁶.
• Solution Steps:³⁴⁷
  1. Detection Mechanism (in BML)³⁴⁸
     • Every decision is classified by group³⁴⁹.
     • Statistical significance test (p < 0.05)³⁵⁰.
     • “Discrimination risk” alarm is triggered³⁵¹.
  2. Impact Analysis³⁵²
     • Which parameters are causing the bias? ³⁵³
     • Which rules have issues? ³⁵⁴
     • Result: “w_k parameter is 0.15 lower for Group X”³⁵⁵.
  3. Remedial Action³⁵⁶
     • Create a group-specific Regional/Local JSON³⁵⁷.
     • Adjust group parameters with Ethics Board approval³⁵⁸.
     • Example: Create TR_Roma_policy.json³⁵⁹.
  4. Monitoring & Verification³⁶⁰
     • Monthly check: Is the discrimination gone? ³⁶¹
     • User satisfaction: Is there an increase? ³⁶²
     • Success: Block rates equalized within 3 months³⁶³.
  5. Public Disclosure³⁶⁴
     • Publish a “Discrimination detected and corrected” report³⁶⁵.
     • Detail which steps were taken³⁶⁶.
     • Right to compensation or apology (if applicable)³⁶⁷.

7. PERFORMANCE INDICATORS (KPIs)

³⁶⁸

8. ROADMAP: THREE VERSIONS

Version 1.0 (Q1-Q2 2026): Basic DERP ³⁶⁹

• Goals:³⁷⁰
  • Establish DERP basic architecture and workflow³⁷¹.
  • Successfully manage the first 100 policy changes via manual triggering³⁷².
  • Standardize the Ethics Board approval process³⁷³.
• Components:³⁷⁴
  • Static Policy Update (manual triggering) ³⁷⁵
  • Basic Audit Record (JSON files) ³⁷⁶
  • Ethics Board approval process ³⁷⁷
  • KPI monitoring and monthly reporting ³⁷⁸
  • DERP Ledger (simple version) ³⁷⁹
• Pilot Applications:³⁸⁰
  • Turkey: Health sector (1-2 hospitals) ³⁸¹
  • EU: Prague or Berlin pilot ³⁸²
• Success Criterion: First 100 policy changes successfully managed (rollback rate < 5%)³⁸³.

Version 2.0 (Q3-Q4 2026): Automation & Dynamism ³⁸⁴

• Goals:³⁸⁵
  • Automatic W-Matrix calibration³⁸⁶.
  • Dynamic cultural change integration (TGNN – Temporal Graph Neural Networks)³⁸⁷.
  • Demonstration of system’s autonomous adaptation³⁸⁸.
• New Components:³⁸⁹
  • Automatic W-Matrix Calibration ³⁹⁰
  • TGNN (To model changes over time) ³⁹¹
  • Policy Draft Sandbox Testing ³⁹²
  • Continuous Anomaly Detection (Real-time drift monitoring) ³⁹³
  • Citizen Panel Automation (Online survey and feedback system) ³⁹⁴
• Pilot Applications:³⁹⁵
  • EU: Various regions ³⁹⁶
  • MENA: Pilot sites ³⁹⁷
  • Asia: Initial tests ³⁹⁸
• Success Criterion: Manual intervention requirement reduced by 50%³⁹⁹.

Version 3.0 (Q1-Q2 2027): Simulation & Foresight ⁴⁰⁰

• Goals:⁴⁰¹
  • Pre-testing of policy changes⁴⁰².
  • Simulation of “What if…” scenarios⁴⁰³.
  • Establishment of a foresight model⁴⁰⁴.
• New Components:⁴⁰⁵
  • Ethical Scenario Simulation (Test before new policy goes live) ⁴⁰⁶
  • Counterfactual Analysis (“What happens if we change this rule in this way?”) ⁴⁰⁷
  • Foresight Model (What changes will be needed in the next 6-12 months) ⁴⁰⁸
  • Multi-Stakeholder Simulation (Modeling reactions of different cultures) ⁴⁰⁹
  • Emergency Simulations (Test how the system behaves in a crisis) ⁴¹⁰
  • War Games (Adversarial scenarios) ⁴¹¹
• Success Criterion: Simulation predictions match real results with 90%+ alignment⁴¹².

9. CONCLUSION: DERP’S ROLE IN ETVZ

DERP (Deep Ethical Regulation Protocol) assumes the role of the “ethical system defense” in the ETVZ ecosystem⁴¹³. It observes the consistency of ethical controls set by HVM and adapts to societal, legal, and cultural changes⁴¹⁴.

CRITICAL POINT: DERP performs all operations Human-in-the-Loop⁴¹⁵. No policy change is applied to the live system without Ethics Board approval⁴¹⁶. Thus, transparency and accountability are ensured in the ethical governance of artificial intelligence⁴¹⁷.

Core Values of DERP: ⁴¹⁸

• Dynamism: Adapting to a changing world. A living system, not a static one⁴¹⁹.
• Transparency: Every change is auditable. A public audit trail⁴²⁰.
• Accountability: Human approval is never bypassed. Multi-sig, veto, rollback⁴²¹.
• Security: Hard constraints are never destabilized. Protective of human life⁴²².
• Societal Participation: Citizen opinion is central. Democracy-first⁴²³.

DERP operates like the “ethical brain” of ETVZ: It observes the ethical decisions filtered by HVM, corrects the incorrect ones, and adapts to the changing world⁴²⁴.