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Artificial Intelligence in Health

PERSPECTIVE ARTICLE
Contextualizing algorithmic literacy framework

for global health workforce education

Seble Frehywot 1,2† * and Yianna Vovides 3†
1 Department of Global Health, School/Faculty, George Washington University, Washington, District
of Colombia, United States of America
2 Department of Health Policy and Management, School/Faculty, George Washington University,
Washington, District of Colombia, United States of America
3 Centers in New Design in Learning and Scholarship, Georgetown University, Washington, District
of Colombia, United States of America

Abstract
With the rapid and accelerating advancement of generative artificial intelligence
(AI), research is lagging on how to ensure that the health workforce becomes and
stays AI-literate. This paper describes a way forward specifically toward establishing
an AI-augmented curriculum within global health workforce education. By global
health workforce education, we refer to the academic staff or faculty and students
in medicine, nursing, global public health, and other health science fields. AI, unlike
other technological advancements, is constantly changing. Therefore, the adoption
† These authors contributed equally of specific tools for health workforce education has to be analyzed in the context
to this work. of the educational setting for shaping a sustainable and equitable AI-augmented
*Corresponding author: global health workforce curriculum. This necessitates an integration of AI algorithmic
Seble Frehywot literacy within academic curricula. In this paper, we propose the algorithmic literacy
(seblelf@gwu.edu) framework (ALF) for global health workforce education to address individual and
Citation: Frehywot S, Vovides Y. organizational readiness. At the individual level, ALF examines one’s knowledge
Contextualizing algorithmic literacy of and skills needed to implement AI within the context of their respective health
framework for global health
workforce education. Artif Intell education expertise. At the organizational level, ALF examines readiness across five
Health. 2025;2(2):41-46. areas: infrastructure and support systems, institutional support, Information and
doi: 10.36922/aih.4903 Communications Technology technical expertise, student engagement, faculty
Received: September 22, 2024 engagement, and analytics technical expertise. ALF offers universities and health
workforce training institutions a way of organizing their approach to algorithmic/
Revised: November 4, 2024
AI literacy readiness that embraces their organization’s values and, at the same time,
Accepted: November 11, 2024 urging them to act.
Published online: November 28,
2024
Keywords: Artificial intelligence; Algorithmic literacy; Medical education; Health sciences
Copyright: © 2024 Author(s). education; Global public health
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution
License, permitting distribution,
and reproduction in any medium, 1. Introduction
provided the original work is
properly cited. Artificial Intelligence (AI) algorithms drive our everyday lives, operating in the
Publisher’s Note: AccScience background and providing personalized services as we interact with our devices and
Publishing remains neutral with apps. While algorithms make significant and positive contributions to society, they often
regard to jurisdictional claims in 1
published maps and institutional lack transparency. Driven by big data and influenced by social, cultural, political, and
affiliations. commercial factors, algorithms have also become powerful gatekeeping tools resulting

Volume 2 Issue 2 (2025) 41 doi: 10.36922/aih.4903