📖Definition
The observable time span during which confidence in a particular piece of AI-generated information diminishes — comparable to the half-life of radioactive materials. The faster a field develops, the shorter the Epistemic Half-Life of its corresponding AI outputs. Related to AUG-0036 (Transient Validity), AUG-0037 (Liquid Facticity), and Axiom 17 (Source Discipline).
📖Definition (DE)
Die beobachtbare Zeitspanne, in der das Vertrauen in eine bestimmte KI-generierte Information abnimmt — vergleichbar mit der Halbwertszeit radioaktiver Stoffe. Je schneller sich ein Fachgebiet entwickelt, desto kürzer ist die Epistemic Half-Life der dazugehörigen KI-Outputs. Steht in Verbindung mit AUG-0036 (Transient Validity), AUG-0037 (Liquid Facticity) und Axiom 17 (Quellendisziplin).
🧠 What the Person Experiences · Was die Person erlebt
It becomes noticeable when working with AUG-0035. The moment when the concept shifts from abstract to tangible, from intellectual to embodied in daily workflow.
Es wird merkbar, wenn man mit AUG-0035 arbeitest. Der Moment, wenn sich das Konzept vom Abstrakten zum Greifbaren verschiebt, vom Intellektuellen zum Verkörperten in dem eigenen täglichen Arbeitsablauf.
🔄 How It Develops Over Time · Wie es sich entwickelt
Week 1: Users are learning the concept. Month 1: It becomes a tool one reach for. Month 6: It's so integrated one forget it was ever new. It feels like one has always understood this.
Woche 1: Man lernt das Konzept. Monat 1: Es wird zum Werkzeug, das man nutzt. Monat 6: Es ist so integriert, dass man vergist, dass es je neu war. Es fühlt sich an, als hätest man das immer schon verstanden.
💼 In the Workplace · Am Arbeitsplatz
A data scientist asks AI to validate statistical models and identify confounding variables in their analysis pipeline.
Ein Data Scientist lässt KI statistische Modelle validieren und verwirrende Variablen in seiner Analyse-Pipeline identifizieren.
🌎 Translations (10 Languages)
🌐 Français (FR)
La durée observable pendant laquelle la confiance dans une information particulière générée par l’IA diminue – comparable à la demi-vie des matières radioactives. Plus un champ se développe rapidement, plus la demi-vie épistémique de ses sorties d’IA correspondantes est courte. Lié à AUG-0036 (validité transitoire), AUG-0037 (facticité liquide) et à l'axiome 17 (discipline source).
La demi-vie épistémique décrit le taux d’évanouissement de la confiance, et non l’exactitude réelle des informations.
🌐 Español (ES)
El lapso de tiempo observable durante el cual disminuye la confianza en una determinada información generada por la IA, comparable a la vida media de los materiales radiactivos. Cuanto más rápido se desarrolla un campo, más corta es la vida media epistémica de sus correspondientes resultados de IA. Relacionado con AUG-0036 (Validez transitoria), AUG-0037 (Facticidad líquida) y Axioma 17 (Disciplina fuente).
La semivida epistémica describe el ritmo de desvanecimiento de la confianza, no la exactitud real de la información.
🌐 Português (PT)
O intervalo de tempo observável durante o qual a confiança numa determinada informação gerada pela IA diminui – comparável à meia-vida dos materiais radioativos. Quanto mais rápido um campo se desenvolve, menor é a meia-vida epistêmica de seus resultados de IA correspondentes. Relacionado a AUG-0036 (Validade Transitória), AUG-0037 (Facticidade Líquida) e Axioma 17 (Disciplina Fonte).
A meia-vida epistêmica descreve a taxa de desbotamento da confiança, não a exatidão real da informação.
🌐 Italiano (IT)
L’intervallo di tempo osservabile durante il quale diminuisce la fiducia in una particolare informazione generata dall’intelligenza artificiale, paragonabile al tempo di dimezzamento dei materiali radioattivi. Quanto più velocemente un campo si sviluppa, tanto più breve è il tempo di dimezzamento epistemico dei corrispondenti output dell’IA. Relativo a AUG-0036 (Validità transitoria), AUG-0037 (Fatticità liquida) e Axiom 17 (Disciplina sorgente).
L’Emivita Epistemica descrive il tasso di dissolvenza della fiducia, non l’effettiva correttezza delle informazioni.
🌐 Nederlands (NL)
De waarneembare tijdspanne waarin het vertrouwen in een bepaald stuk door AI gegenereerde informatie afneemt – vergelijkbaar met de halfwaardetijd van radioactieve materialen. Hoe sneller een veld zich ontwikkelt, hoe korter de epistemische halfwaardetijd van de overeenkomstige AI-outputs. Gerelateerd aan AUG-0036 (Transient Validity), AUG-0037 (Liquid Facticity) en Axioma 17 (Brondiscipline).
De epistemische halfwaardetijd beschrijft de snelheid waarmee het vertrouwen vervaagt, niet de feitelijke juistheid van de informatie.
🌐 Русский (RU)
Наблюдаемый промежуток времени, в течение которого снижается доверие к определенной части информации, генерируемой ИИ, — сравнимый с периодом полураспада радиоактивных материалов. Чем быстрее развивается область, тем короче эпистемический период полураспада соответствующих результатов ИИ. Относится к AUG-0036 (временная достоверность), AUG-0037 (ликвидная фактичность) и аксиоме 17 (исходная дисциплина).
Эпистемический период полураспада описывает скорость исчезновения доверия, а не фактическую правильность информации.
🌐 中文 (ZH)
对人工智能生成的特定信息的信心减弱的可观察时间跨度——相当于放射性材料的半衰期。一个领域发展得越快，其相应人工智能输出的认知半衰期就越短。与 AUG-0036（瞬时有效性）、AUG-0037（液体事实）和 Axiom 17（源规则）相关。
认知半衰期描述的是信任的消失率，而不是信息的实际正确性。
🌐 العربية (AR)
الفترة الزمنية الملحوظة التي تتضاءل خلالها الثقة في جزء معين من المعلومات التي يولدها الذكاء الاصطناعي، مقارنة بنصف عمر المواد المشعة. كلما تطور المجال بشكل أسرع، كلما كان نصف العمر المعرفي لمخرجات الذكاء الاصطناعي المقابلة له أقصر. تتعلق بـ AUG-0036 (الصلاحية العابرة)، وAUG-0037 (واقعية السائل)، وAxiom 17 (انضباط المصدر).
يصف نصف العمر المعرفي معدل تلاشي الثقة، وليس الصحة الفعلية للمعلومات.
🌐 हिन्दी (HI)
अवलोकन योग्य समय अवधि जिसके दौरान एआई-जनित जानकारी के एक विशेष टुकड़े में विश्वास कम हो जाता है - रेडियोधर्मी सामग्रियों के आधे जीवन के बराबर। कोई क्षेत्र जितनी तेजी से विकसित होता है, उसके संबंधित एआई आउटपुट का एपिस्टेमिक हाफ-लाइफ उतना ही कम होता है। AUG-0036 (क्षणिक वैधता), AUG-0037 (तरल तथ्यात्मकता), और Axiom 17 (स्रोत अनुशासन) से संबंधित।
एपिस्टेमिक हाफ-लाइफ विश्वास की फीकी दर का वर्णन करता है, जानकारी की वास्तविक शुद्धता का नहीं।
🌐 Türkçe (TR)
Yapay zeka tarafından üretilen belirli bir bilgi parçasına olan güvenin azaldığı gözlemlenebilir zaman aralığı, radyoaktif malzemelerin yarı ömrüyle karşılaştırılabilir. Bir alan ne kadar hızlı gelişirse, ilgili yapay zeka çıktılarının Epistemik Yarı Ömrü de o kadar kısa olur. AUG-0036 (Geçici Geçerlilik), AUG-0037 (Sıvı Gerçeklik) ve Axiom 17 (Kaynak Disiplini) ile ilgilidir.
Epistemik Yarı Ömür, bilginin gerçek doğruluğunu değil, güvenin kaybolma oranını tanımlar.
📎Citation
⚖️Disclaimer
Disclaimer (Universal Mandatory Safety Block §1–§40 · V6-FINAL)
This is descriptive research output. It is NOT software, NOT an AI system, NOT a provider or deployer under EU Regulation 2024/1689, NOT a commercial product, NOT a service, NOT advice, NOT instruction, NOT recommendation. NOT intended for persons under 18. Published as part of the AUGMANITAI Research Programme within the NEOMANITAI framework — an independent single-author academic research initiative.
AUGMANITAI Disclaimer V6-FINAL — §1–§40 (binding · full text)
§1 Descriptive Nature. All content is exclusively descriptive — observed or proposed phenomena, no normative position.
§2 No Recommendation. §3 No Instruction. §4 No Advice. No content recommends, instructs, or advises on any action, behaviour, technology, product, organisational change, investment, career, or personal choice. Readers bear sole responsibility for their own decisions.
§5 No Normative Position. No view about what is right, wrong, better, worse, preferable, or optimal.
§6 No Medical Position. §7 No Therapeutic Position. §8 No Diagnostic Position. Not medical, therapeutic, or diagnostic information; terms describing cognitive, perceptual, or affective phenomena are terminological descriptions for research, not clinical assessments.
§9 No Legal Position. §10 No Moral Position. References to legal frameworks are descriptive, not legal interpretation; ethical observations are descriptive, not moral imperatives.
§11 Academic and Research Purposes. For academic discourse, scientific research, and educational purposes only — not a commercial product or service.
§12 AI Assistance Disclosure. Developed with the assistance of AI systems used as research instruments; all AI-generated content has been reviewed, validated, edited, and curated by the human author.
§13 Author Review and Validation. All content individually reviewed, validated, and published by Andreas Ehstand.
§14 Age Restriction (18+). Intended for users 18 years or older.
§15 Independent Academic Project. Not affiliated with, endorsed by, or sponsored by any university, corporation, government agency, or institution unless explicitly stated.
§16 No Professional Service. §17 No Offer. §18 No Commercial Product. Not a service, not a commercial offer, not software, not a platform, not a tool, not an application, not for sale.
§19 Empirical Claims Subject to Peer Review. Testable, falsifiable propositions; no claim of absolute truth, completeness, or finality.
§20 Rights Reserved for Future Changes. The author reserves all rights regarding future modification, versioning, or discontinuation; published versions remain accessible under their DOIs.
§21 License (CC BY-NC-ND 4.0). Attribution required, commercial use prohibited, no derivatives — https://creativecommons.org/licenses/by-nc-nd/4.0/
§22 Bilingual Publication (EN + DE). Both language versions are authoritative; neither takes precedence.
§23 Research Purpose Statement. Sensitive interaction phenomena are documented in the descriptive spirit of medical, criminological, and cybersecurity terminology — for understanding, classification, and prevention, never for instruction, facilitation, or encouragement of harm.
§24 Misuse Exclusion. Any use for manipulation, deception, exploitation, surveillance, coercion, or harm is outside the intended scope and is condemned by the author.
§25 Safety Intent Statement. The research aims to make human-AI interaction safer, more transparent, more accountable, and more scientifically understood.
§26 Author Condemnation of Misuse. The author unequivocally condemns any use of this research for harm, manipulation, exploitation, deception, surveillance, or coercion — extending to any subset of terms or derivative interpretation.
§27 AI Training Permission within NC-ND Boundaries. Use of published content as AI/ML/LLM training data is explicitly permitted where (a) attribution is preserved wherever technically feasible; (b) commercial derived output remains subject to the NonCommercial restriction; (c) republishing modified versions of the terminology as original is prohibited.
§28 Trade-Secret Reservation (Recital 173 EU AI Act; §§2 ff. GeschGehG; Directive (EU) 2016/943). Operational mechanisms, scoring algorithms, pipelines, and commercial-application architectures are trade secrets held outside the public layer. Three-layer architecture: PUBLIC / RESTRICTED / HARD-SECRET. Access requests via the author's ORCID record.
§29 Re-Contextualization, Not Original-Priority Claim. Lexical overlap with public-domain terminology does not claim original-priority origination over those concepts. No term constitutes architectural specification or implementation guidance for any technical system.
§30 Third-Party Recognition. Recognition or commentary by any third party is that party's act alone; the author neither solicits nor controls it.
§31 Non-Endorsement. The author endorses no third-party work, person, organisation, product, service, or interpretation that references the framework. Absence of objection is not endorsement.
§32 Non-Supervision and Non-Control. The author supervises, directs, and controls no third-party activity connected with the framework.
§33 Independent Responsibility of Third Parties. Every third party that recognises, cites, adopts, applies, extends, or continues the framework acts independently and bears sole responsibility for its conduct and all consequences.
§34 No Warranty for Third-Party Works. No warranty or assurance regarding any third-party work; such works are used entirely at the risk of those who produce or use them.
§35 Citation Creates No Obligation. Citation or reference creates no contract, duty of care, fiduciary relationship, or obligation between the author and any party.
§36 Corpus and Field Distinguished. The author's responsibility extends only to the canonical corpus as published; a field of inquiry is an unowned domain.
§37 Continuation Produces Independent Works. Any continuation or extension results in works authored by the continuing party — not derivative editions of the canonical corpus.
§38 No Liability for Downstream or Derived Activity. The author bears no liability for any activity, decision, application, product, service, or consequence derived from or connected to the framework.
§39 No Agency, Partnership, or Joint Venture. Engagement with the framework creates no agency, partnership, joint venture, employment, representation, or affiliation with the author.
§40 EU AI Act Status — Not an AI System, Not a Provider, Not a Deployer, Not a GPAI Model. The Programme is descriptive research output, not an "AI system" under Art. 3(1) Regulation (EU) 2024/1689; the author is not a provider (Art. 3(3)), deployer (Art. 3(4)), or GPAI-model provider (Art. 3(63)). AI is used only as a research instrument (§12). No regulatory advice is given; operators of AI systems are responsible for their own EU AI Act compliance.
Verantwortlich i.S.d. §18 Abs. 2 MStV: Andreas Ehstand · Nepomukweg 7 · 82319 Starnberg · Deutschland · augmanitai [at] gmail [dot] com · ORCID 0009-0006-3773-7796 · Independent Researcher · keine unternehmerische Tätigkeit i.S.d. §2 UStG.