APi Working Paper No. 1 (March, 2026)
Title: Appearance Epidemiology: A Conceptual Framework for Understanding the Distribution and Determinants of Appearance-Based Inequality.
Author: Ogo Maduewesi
Description:
This working paper introduces Appearance Epidemiology (AE), an interdisciplinary framework that conceptualises involuntary visible traits as structured exposure variables operating across cultural, institutional, and structural systems.
The paper establishes appearance as a population-level determinant of psychosocial well-being, dignity, and opportunity and lays the conceptual foundation for the field.
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Keywords:
Appearance Epidemiology • Lookism • Psychosocial Well-being • Social Equity • Visible Difference • Skin Condition • Appearance Differences
APi Working Paper No. 2 (April, 2026)
Title: When AI Misreads the Human Face: Algorithmic Homogenization and the Erasure of Human Appearance Differences
Author: Ogo Maduewesi
Description:
This working paper examines how generative AI systems fail to accurately represent human appearance differences; particularly visible differences, skin conditions, and African appearance diversity. It introduces the concept of Algorithmic Homogenization: the structural tendency of AI systems to converge human appearance representation toward narrow norms, treating visible difference as deviation to be corrected rather than valid human variation. The paper documents the psychosocial consequences of this pattern and proposes an appearance-centered framework for AI accountability.
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APi Working Paper No. 1 Verson 2.0 (June, 2026)
Title: Appearance Epidemiology: A Provocation
Author: Ogo Maduewesi
Description:
This working paper explores how Appearance-based inequality shapes who gets hired, who gets treated, who gets loved, and who gets erased. It is a primary stratification system whose consequences have been systematically underestimated-comparable in structure and consequence to race, class, and gender, yet almost entirely absent from the frameworks built to study them. That absence is not accidental. It reflects structural patterns in how inequality is defined, measured, and prioritised, patterns that have kept appearance off the research agenda, out of the funding conversation, and invisible in policy. This paper names those patterns directly. .
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