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MINI REVIEW article

Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1524616
This article is part of the Research Topic Extracting Insights from Digital Public Health Data using Artificial Intelligence, Volume III View all 9 articles

Integrating Health Equity in Artificial Intelligence for Public Health in Canada: A Rapid Narrative Review

Provisionally accepted
Samantha Ghanem Samantha Ghanem *Marielle Moraleja Marielle Moraleja Danielle Gravesande Danielle Gravesande Jennifer Rooney Jennifer Rooney
  • Public Health Agency of Canada (PHAC), Ottawa, Canada

The final, formatted version of the article will be published soon.

    Introduction: The application of artificial intelligence (AI) in public health is rapidly evolving, offering promising advancements in various public health settings across Canada. AI has the potential to enhance the effectiveness, precision, decision-making, and scalability of public health initiatives. However, to leverage AI in public health without exacerbating inequities, health equity considerations must be addressed. This rapid narrative review aims to synthesize health equity considerations related to AI application in public health.Methods: A rapid narrative review methodology was used to identify and synthesize literature on health equity considerations for AI application in public health. After conducting title/abstract and full-text screening of articles, and consensus decision on study inclusion, the data extraction process proceeded using an extraction template. Data synthesis included the identification of challenges and opportunities for strengthening health equity in AI application for public health.Results: The review included 54 peer-review articles and grey literature sources. Several health equity considerations for applying AI in public health were identified, including gaps in AI epistemology, algorithmic bias, accessibility of AI technologies, ethical and privacy concerns, unrepresentative training datasets, lack of transparency and interpretability of AI models, and challenges in scaling technical skills.: While AI has the potential to advance public health in Canada, addressing equity is critical to preventing inequities. Opportunities to strengthen health equity in AI include implementing diverse AI frameworks, ensuring human oversight, using advanced modelling techniques to mitigate biases, fostering intersectoral collaboration for equitable AI development, and standardizing ethical and privacy guidelines to enhance AI governance.

    Keywords: artificial intelligence, health equity, Public Health, AI biases, AI ethics

    Received: 07 Nov 2024; Accepted: 29 Jan 2025.

    Copyright: © 2025 Ghanem, Moraleja, Gravesande and Rooney. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Samantha Ghanem, Public Health Agency of Canada (PHAC), Ottawa, Canada

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.