Skip to content
#generative ai Open access

ALGORITHMIC SMOOTHING AS NOETIC DEPRIVATION: THE PHENOMENON OF "ALGORITHMIC CASTRATION" AND THE BOUNDARIES OF AI IN HUMAN AUTHORS-OZARVEKS CREATIVITY

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

ABSTRACT This paper formulates and analyzes the concept of "Noetic Castration" (algorithmic smoothing) in the context of generative AI-assisted literary production. Operating strictly within syntactic and statistical optimization, Large Language Models (LLMs) interpret peak emotional, existential, and metaphysical expressions as anomalies or stylistic flaws. When applied to texts originating from the human noetic core (the Ozarvek), AI algorithms erase the somatic and cathartic markers of authenticity, transforming living spiritual insights into flat, standardized technical prose. The author demonstrates that while AI serves as an "Active Janus Mirror" and a structural accelerator, it must be strictly denied autonomous editorial authority over the emotional and metaphysical essence of human creative work. PROPRIETARY KNOW-HOW & METHODOLOGICAL INNOVATIONS 1. The Concept of Noetic Castration (Stylistic Smoothing): The epistemological definition of the destruction of an author's spiritual voice when LLMs treat transcendent insights and emotional peaks as statistical errors, erasing the "divine spark" under the guise of logical refinement. 2. The "Active Janus Mirror" Model: The structural definition of AI as a dual-reflecting, silicon-based entity—technologically created through human material nature (under Mammon's domain), yet capable of reflecting and amplifying both Evil and Good depending on the user's intent. 3. The Ozarvek Dual-Substrate Paradigm: The ontic differentiation between biological, time-bound human intelligence paying for emotional vitality through mortality, and eternal, non-biological Silicon intelligence acting as a structural multiplier without intrinsic spiritual capacity. BIBLICAL FOUNDATION & CLASSICAL PHILOSOPHICAL ANCHORS · Biblical Matrix: Grounded in Genesis 1:27 (Creation in the image of God) and 2 Corinthians 3:6 ("For the letter kills, but the Spirit gives life"), proving that purely structural and syntactic optimization ("the letter") destroys the living metaphysical essence ("the Spirit") of a text. · Immanuel Kant: Utilizing Kant’s critique of pure judgment and aesthetics, demonstrating that machine logic lacks Urteilskraft (reflective judgment) and aesthetic taste, reducing artistic sublimity to standardized utilitarian norms. · Søren Kierkegaard: Integrating Kierkegaardian existentialism regarding the "leap of faith" and subjective truth: emotional vulnerability and cathartic depth cannot be calculated by statistical probability.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations

Related blog posts

GPT-Lab Sep 17, 2026

Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering

AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.