ETVZ

RLHF’in Ötesi: Büyük Dil Modellerine “Hesaplamalı Vicdan” Mimarisi Entegrasyonu (ETVZ Teknik Derlemesi)

ETVZ Mimarisi; Hesaplamalı Vicdan Modülü (HVM); Büyük Dil Modelleri Entegrasyonu; LLM Denetim Katmanı; Epistemik Hafıza ve RAG; NLP Mühendisliği; RLHF Alternatifleri

Yazar: Göktürk KADIOĞLU Tarih: Aralık 2025 Yönetici Özeti (Abstract) Mevcut Büyük Dil Modelleri (LLM’ler), “bir sonraki token tahmini” (next-token prediction) prensibiyle çalışan güçlü stokastik motorlardır. Ancak bu modeller, ürettikleri çıktıların anlamsal doğruluğunu veya etik sonuçlarını içsel olarak “muhakeme” yeteneğine sahip değildir. Mevcut hizalama (alignment) teknikleri—örneğin RLHF (Reinforcement Learning from Human Feedback)—genellikle modelin ağırlıklarına gömülü statik […]

Ethics-Based Conscientious Intelligence (ETVZ): Integrating Computational Conscience into AI — A Mathematical and Operational Framework

ETVZ, Ethics-Based Conscientious Intelligence, Computational Conscience, HVM, AI Safety, AI Alignment, Human-in-the-loop, Mathematical Framework for AI Ethics, Multi-objective Optimization, Instrumental Convergence, Göktürk Kadıoğlu,

Göktürk Kadıoğlu (Conceptual Lead) – Dr.Ahmet Albayrak Prepared with AI Collaborator ETVZ Research Initiative November 2, 2025 Abstract This paper presents the Ethics-Based Conscientious Intelligence (ETVZ) paradigm: a technical, philosophical, and operational framework for integrating computational conscience into high-capacity AI systems. As a critical clarification, we emphasize that ETVZ systems never operate as autonomous decision-makers […]

CHAPTER 3 — HVM (Computational Conscience Module): The Core Decision Engine of ETVZ

3.1 The Logic of Human Conscience: “Pause, Reflect, Evaluate, Then Decide” Human decision-making involves an instinctive multi-stage process before reaching judgment: The Hesaplamalı Vicdan Modülü (HVM) transforms this chain into a mathematical architecture, enabling artificial intelligence to learn, for the first time, the capacities to “pause,” “reflect,” and “conduct ethical pre-screening” before response generation. HVM […]

CHAPTER 4 — DERP & DERMS: Ethical Regulation, Deviation Detection, and Dynamic Risk Surveillance

4.1 The Most Dangerous Deficit in Artificial Intelligence: “Undetected Deviation” Even initially secure artificial intelligence systems are susceptible to temporal degradation through multiple vectors: Humans possess intuitive mechanisms for detecting such deviations. Artificial intelligence, however, requires explicit architectural safeguards to achieve equivalent detection capabilities. DERP (Dynamic Ethical Regulation and Policy Engine) and DERMS (Dynamic Ethical […]

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 […]

DERMS: DYNAMIC ETHICAL RISK MONITOR SYSTEM

Proactive Ethical Oversight, Anomaly Detection, and Automated Intervention Mechanisms ETVZ Research Initiative | Istanbul, Turkey | November 2025 ABSTRACT AI-based ethical decision-making systems are becoming prevalent in critical fields such as medicine, law, education, and finance. However, mechanisms that monitor their ethical performance in real-time and conduct proactive risk management are lacking. DERMS (Dynamic Ethical […]

HVM: COMPUTATIONAL CONSCIENCE MODULE

Multi-Dimensional Ethical Control, Deontic Rule Application, and Human-Centric Decision-Making in AI Systems 2 ETVZ Research Initiative | Istanbul, Turkey | November 2025 ABSTRACT Artificial intelligence systems, LLMs, and autonomous agents have increasingly begun to make decisions in complex domains5. However, ensuring that the outputs of these systems are passed through an ethical filter and remain […]

CHAPTER 5 — Cultural Context: The Context Analyzer (CA)

5.1 The Most Overlooked Reality in Artificial Intelligence: Culture is Everything The meaning of a sentence is not determined by its lexical components but by its cultural embedding. Identical linguistic utterances generate radically different semantic and affective interpretations across cultural contexts: Contemporary artificial intelligence systems treat culture as a universal constant—an approach fundamentally misaligned with […]

EPISTEMIC MEMORY: A NEO4J-BASED ETHICAL KNOWLEDGE GRAPH

Security Architecture, Trust Score Mechanism, and Temporal Graph Neural Network Integration for the ETVZ Framework Technical Design Document v2.0 ETVZ Research Initiative | Istanbul, Turkey | November 2025 ABSTRACT Contemporary Large Language Models (LLMs), despite their remarkable text generation capabilities, face substantial challenges regarding hallucination (presenting nonexistent information as factual) and epistemic groundlessness (inability to […]

CHAPTER 6 — Manipulation Detection, Security Architecture, and Verification Systems

ETVZ’s Protective Shield, Defensive Consciousness, and Reality Control Mechanisms 6.1 The Greatest Risk in Artificial Intelligence: “Unconscious” Model Manipulation Contemporary Large Language Models are highly susceptible to adversarial influence through multiple manipulation vectors: Manipulation taxonomies: Under such manipulation, models exhibit characteristic degradation patterns: ETVZ’s security architecture is designed for proactive detection and mitigation of these […]