Inferred Attribute Leakage

Term ID: MKT-0039 · Category: Marketing_AI · Confidence: 0.92 (0.92) · Band: extended
Author: Andreas Ehstand · ORCID: 0009-0006-3773-7796 · DOI: 10.5281/zenodo.14888381
CC BY-NC-ND 4.0 0.92 Marketing_AI Bilingual EN/DE DOI: 10.5281/zenodo.14888381

Definition (English)

Algorithmic systems infer sensitive attributes — health, sexuality, political views — from superficially innocuous behavioral signals, and marketers target on these inferences without the audience ever having disclosed the attributes. This inference leakage circumvents privacy frameworks built around explicit data categories, because the sensitive information was produced by the system rather than collected from the user.

Definition (Deutsch)

Algorithmische Systeme leiten sensible Attribute — Gesundheit, Sexualität, politische Ansichten — aus oberflächlich harmlosen Verhaltenssignalen ab, und Vermarkter targeten auf diese Inferenzen, ohne dass Publikum die Attribute offenlegte. Diese Inferenz-Leckage umgeht Datenschutzrahmen, die um explizite Datenkategorien gebaut wurden.

Metadata

Term IDMKT-0039
English NameInferred Attribute Leakage
German NameInferierte-Attribut-Leckage
CategoryMarketing_AI
Confidence0.92 (0.92)
Bandextended
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/inferred-attribute-leakage.html

Semantic Relations

Cross-Domain Connections

Enrichment bias propagation Accessibility Data Privacy Amplification The Algorithmic Filter

Distinct From (Not to Be Confused With)

Validation Set Leakage Blindness Abstraction Leakage Acceptance Input Autocomplete Attribute Omission

Citation

APA 7th

Ehstand, A. (2026). Inferred Attribute Leakage. In AUGMANITAI: A Compendium for Human-AI Interaction Terminology (MKT-0039). https://doi.org/10.5281/zenodo.14888381

MLA 9th

Ehstand, Andreas. "Inferred Attribute Leakage." AUGMANITAI: A Compendium for Human-AI Interaction Terminology, 2026. MKT-0039. doi:10.5281/zenodo.14888381.

Chicago 17th

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

BibTeX

@misc{augmanitai_mkt_0039, author = {Ehstand, Andreas}, title = {Inferred Attribute Leakage}, year = {2026}, howpublished = {AUGMANITAI Compendium (MKT-0039)}, doi = {10.5281/zenodo.14888381}, url = {https://andreasehstandlicenseofclarityloc.github.io/neomanitai-terms/academic/inferred-attribute-leakage.html}, license = {CC BY-NC-ND 4.0} }

RIS

TY - ELEC AU - Ehstand, Andreas TI - Inferred Attribute Leakage PY - 2026 DO - 10.5281/zenodo.14888381 UR - https://andreasehstandlicenseofclarityloc.github.io/neomanitai-terms/academic/inferred-attribute-leakage.html AB - Algorithmic systems infer sensitive attributes — health, sexuality, political views — from superficially innocuous behavioral signals, and marketers target on these inferences without the audience ever having disclosed the attributes. This inference leakage circumvents privacy frameworks built around explicit data categories, because the sensitive information was produced by the system rather than collected from the user. KW - Human-AI Interaction KW - Marketing_AI ER -

How to Cite This Term

Recommended (APA 7th): Ehstand, A. (2025). Inferred Attribute Leakage. In AUGMANITAI: A Compendium of Relational Phenomenology for Human-AI Interaction (MKT-0039). 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 2,000+ DOI-registered terms across dozens of 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)

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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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