Citation

Tinco Aliaga, César Abelardo and Tan, Myles Joshua Toledo and Hinostroza Fuentes, Vasco Gerardo and Abdul Karim, Hezerul and AlDahoul, Nouar (2026) AI without representation is just inequity at scale: on the exportation of unrepresentative artificial intelligence models to the Global South. Frontiers in Artificial Intelligence, 9. ISSN 2624-8212

Text AI without representation is just inequity at scale_ on the exportation of unrepresentative artificial intelligence models to the Global South.pdf - Published Version Restricted to Repository staff only Download (534kB)

Abstract

A common assumption in discussions of artificial intelligence (AI) is that increasing demographic representation in training data is sufficient to mitigate bias. Under this view, failures in facial recognition, clinical classification, and language generation are treated primarily as problems of coverage that can be resolved through more inclusive sampling. While intuitively appealing, this assumption becomes problematic when models trained and validated within one sociotechnical context are deployed into others whose realities were never meaningfully represented during development. This limitation is particularly evident in health-related AI, where outcomes are shaped not only by biological variables but also by lifestyle and environmental factors that interact dynamically over time, challenging purely data-centric notions of representation

Item Type:	Article
Uncontrolled Keywords:	AI governance, algorithmic fairness, artificial intelligence equity
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Sep 2026 08:24
Last Modified:	02 Sep 2026 08:24
URII:	http://shdl.mmu.edu.my/id/eprint/16547

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