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The Inreliant Win

Term ID: TRU-0008 · Category: Trust_AI · Confidence: Inferred (I) · Band: Trust AI
Author: Andreas Ehstand · ORCID: 0009-0006-3773-7796 · DOI: 10.5281/zenodo.14888381
CC BY-NC-ND 4.0 Inferred Trust_AI Bilingual EN/DE DOI: 10.5281/zenodo.14888381

Definition (English)

Success in mastering a task without AI support, especially when the user was previously reliant on AI assistance. This demonstrates genuine skill transfer, not just delegation.

Metadata

Term IDTRU-0008
English NameThe Inreliant Win
German NameThe Inreliant Win
CategoryTrust_AI
ConfidenceInferred (I)
BandTrust AI
LanguagesEnglish, Deutsch
LicenseCC BY-NC-ND 4.0 International
DOI10.5281/zenodo.14888381
ORCID0009-0006-3773-7796
CompendiumAUGMANITAI — Human-AI Interaction Terminology
Date Published2026-04-04
Permalinkhttps://andreasehstandlicenseofclarityloc.github.io/neomanitai-terms/academic/the-inreliant-win.html

Semantic Relations

Cross-Domain Connections

The Delegation Depth The Confidence Borrow The Trust Calibration The Invisible Wingman

Distinct From (Not to Be Confused With)

The Micro Win The Debate Win The Inreliant Mode

Citation

APA 7th

Ehstand, A. (2026). The Inreliant Win. In AUGMANITAI: A Compendium for Human-AI Interaction Terminology (TRU-0008). https://doi.org/10.5281/zenodo.14888381

MLA 9th

Ehstand, Andreas. "The Inreliant Win." AUGMANITAI: A Compendium for Human-AI Interaction Terminology, 2026. TRU-0008. doi:10.5281/zenodo.14888381.

Chicago 17th

Ehstand, Andreas. "The Inreliant Win." In AUGMANITAI: A Compendium for Human-AI Interaction Terminology. 2026. https://doi.org/10.5281/zenodo.14888381.

BibTeX

@misc{augmanitai_tru_0008, author = {Ehstand, Andreas}, title = {The Inreliant Win}, year = {2026}, howpublished = {AUGMANITAI Compendium (TRU-0008)}, doi = {10.5281/zenodo.14888381}, url = {https://andreasehstandlicenseofclarityloc.github.io/neomanitai-terms/academic/the-inreliant-win.html}, license = {CC BY-NC-ND 4.0} }

RIS

TY - ELEC AU - Ehstand, Andreas TI - The Inreliant Win PY - 2026 DO - 10.5281/zenodo.14888381 UR - https://andreasehstandlicenseofclarityloc.github.io/neomanitai-terms/academic/the-inreliant-win.html AB - Success in mastering a task without AI support, especially when the user was previously reliant on AI assistance. This demonstrates genuine skill transfer, not just delegation. KW - Human-AI Interaction KW - Trust_AI ER -

How to Cite This Term

Recommended (APA 7th): Ehstand, A. (2025). The Inreliant Win. In AUGMANITAI: A Compendium of Relational Phenomenology for Human-AI Interaction (TRU-0008). https://doi.org/10.5281/zenodo.14888381

All citation formats available above. For BibTeX/RIS export, see augmanitai_all.bib or augmanitai.ris.

About This Resource

Part of the first comprehensive terminology framework for Human-AI Interaction phenomena. The AUGMANITAI Compendium contains 4,618 DOI-registered terms across 43 subject areas in up to 12 languages — the largest structured knowledge resource for relational, cognitive, and systemic patterns between humans and AI systems. Created by Andreas Ehstand (ORCID: 0009-0006-3773-7796, Wikidata: Q138634675), published via Zenodo with 5 DOIs, ISO 704/1087/30042-compatible, and accompanied by an OWL ontology and SKOS vocabulary.

FAIR Data Compliance: Findable (5 DOIs, ORCID, Wikidata Q138634675, sitemap, Google Scholar tags) · Accessible (open HTML, JSON-LD, RDF, Turtle, CSV, BibTeX, RIS, JSONL — no login required) · Interoperable (Schema.org, SKOS, Dublin Core, OWL, ISO 704/1087/30042) · Reusable (CC BY-NC-ND 4.0, CITATION.cff, 90+ machine-readable metadata elements per page)

Machine-Readable Formats

JSON-LD (inline)Embedded in this page <script type="application/ld+json">
SKOS/RDFa (inline)Embedded in this page <meta property="skos:*"> (2 languages)
JSON-LD (bulk)augmanitai.jsonld (Schema.org, all terms)
RDF/XML (bulk)augmanitai.rdf (SKOS)
Turtle (bulk)augmanitai.ttl (RDF)
BibTeX (bulk)augmanitai_all.bib
RIS (bulk)augmanitai.ris
CSV (bulk)augmanitai_terms.csv
JSONL/HuggingFaceaugmanitai_dataset.jsonl
API JSONapi_terms.json
Sitemapsitemap.xml
Atom Feedfeed.xml
CITATION.cffCITATION.cff
llms.txtllms.txt

Disclaimer (EN)

§1 This term documents an observable or predicted phenomenon. It is descriptive, not prescriptive. §2 This term does not advocate for or against any educational, institutional, or pedagogical approach. §3 The definition is a descriptive observation or logical inference, not an empirical claim unless marked (D). §4 References to data collection or surveillance describe phenomena for academic purposes. GDPR applies. §5 This term does not constitute medical, psychological, psychiatric, or clinical advice. §6 All trademarks are property of their respective owners. No endorsement implied. §7 Terms addressing inequality document systemic patterns without attributing fault. §8 References to cognitive development or wellbeing are academic observations, not clinical guidance. §9 Numerical values are approximate references. Verify current data independently. §10 This term does not constitute legal advice. §11 CC BY-NC-ND 4.0 International. No derivatives. No commercial use without permission. §12 Definition developed with AI assistance. Reviewed and approved by the author. §13 No guarantee of completeness or accuracy. Information reflects the state at publication. §14 Cultural contexts may differ across regions and languages. §15 Intended for adult users (18+) in academic or professional contexts. §16 The author assumes no liability for decisions based on this terminology. §17 The author reserves the right to modify or remove terms without notice. §18 Part of the AUGMANITAI compendium for Human-AI Interaction terminology. §19 German law applies. Jurisdiction: Federal Republic of Germany. §20 Severability: If any provision is invalid, remaining provisions remain in effect.

Haftungsausschluss (DE)

§1 Dieser Term dokumentiert ein beobachtbares oder prognostiziertes Phänomen. Deskriptiv, nicht präskriptiv. §2 Dieser Term tritt nicht für oder gegen einen pädagogischen Ansatz ein. §3 Die Definition ist eine beschreibende Beobachtung oder logische Schlussfolgerung. §4 Bezüge zu Datenerhebung beschreiben Phänomene für akademische Zwecke. DSGVO gilt. §5 Dieser Term stellt keine medizinische oder klinische Beratung dar. §6 Alle Markenzeichen sind Eigentum ihrer jeweiligen Inhaber. §7 Terme zu Ungleichheit dokumentieren systemische Muster ohne Schuldzuweisung. §8 Bezüge zu kognitiver Entwicklung sind akademische Beobachtungen. §9 Numerische Werte sind ungenähre Referenzen. §10 Dieser Term stellt keine Rechtsberatung dar. §11 CC BY-NC-ND 4.0 International. Keine Bearbeitungen. Keine kommerzielle Nutzung. §12 Definition mit KI-Unterstützung entwickelt. Vom Autor überprüft und freigegeben. §13 Keine Garantie für Vollständigkeit oder Richtigkeit. §14 Kulturelle Kontexte können sich regional unterscheiden. §15 Für erwachsene Nutzer (18+) in akademischen oder professionellen Kontexten. §16 Der Autor übernimmt keine Haftung für Entscheidungen auf Grundlage dieser Terminologie. §17 Der Autor behält sich das Recht vor, Terme jederzeit zu ändern oder zu entfernen. §18 Teil des AUGMANITAI-Kompendiums für Human-AI-Interaktionsterminologie. §19 Es gilt deutsches Recht. Gerichtsstand: Bundesrepublik Deutschland. §20 Salvatorische Klausel: Übrige Bestimmungen bleiben wirksam.

Impressum (DDG §5 / §18 Abs. 2 MStV)

Andreas Ehstand

Nepomukweg 7, 82319 Starnberg, Deutschland

ORCID: 0009-0006-3773-7796

Contact: augmanitai [at] gmail [dot] com

Verantwortlich für den Inhalt nach §18 Abs. 2 MStV: Andreas Ehstand

DOI: 10.5281/zenodo.14888381

Jurisdiction: Bundesrepublik Deutschland

© 2026 Andreas Ehstand. CC BY-NC-ND 4.0 International.

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