The Algorithmic Blind Spot: Why Artificial Intelligence Needs Data from LMICs – A Call for Papers
Year: 2026
Type: paratext
Abstract: Brain health is an emerging global challenge, which has strong implications for the development and implementation of artificial intelligence (AI) in medicine. To date, advances in medicine driven by data from high income countries have shaped everything downstream: what conditions are studied, what populations are enrolled, what tools are validated. This is a problem beyond simple underrepresentation; it is a problem of algorithmic drift. The algorithms generated by AI will not be adequately trained for lower-and middle-income country (LMIC) scenarios unless data from LMICs make their way into the algorithm. Bridging this algorithmic gap requires publication of locally generated, interpreted, and context-specific evidence from LMICs to ensure representation from the majority of the global population.
Source: Journal of Brain Health
DOI: 10.65104/001c.162204
Author: Kathleen M Hayden
Institution: Trinity College Dublin
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7161605004