{"title":"[Artificial intelligence in Public Health: opportunities, ethical challenges and future perspectives].","authors":"Sergio Castaño Castaño","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze large volumes of data in real time enhances epidemiological surveillance, optimizes healthcare resource management, and personalizes preventive interventions. These applications have proven valuable in situations such as pandemics, where AI algorithms have contributed to outbreak prediction, efficient resource allocation, and the design of targeted strategies. However, the adoption of AI also raises significant ethical and regulatory challenges. Issues such as data privacy, algorithmic transparency, and biases in models highlight the need for robust regulatory frameworks to ensure its ethical and equitable use. Furthermore, the lack of training among Public Health professionals and the digital literacy of communities limit the potential impact of these technologies. This article examines the practical applications, ethical challenges, and strategies needed for the responsible adoption of AI in Public Health. It emphasizes the importance of training, interdisciplinary collaboration, and continuous research to ensure that AI becomes a transformative tool contributing to global well-being. If implemented ethically and sustainably, AI can play a crucial role in promoting equity and quality in Public Health systems.</p>","PeriodicalId":94199,"journal":{"name":"Revista espanola de salud publica","volume":"99 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista espanola de salud publica","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze large volumes of data in real time enhances epidemiological surveillance, optimizes healthcare resource management, and personalizes preventive interventions. These applications have proven valuable in situations such as pandemics, where AI algorithms have contributed to outbreak prediction, efficient resource allocation, and the design of targeted strategies. However, the adoption of AI also raises significant ethical and regulatory challenges. Issues such as data privacy, algorithmic transparency, and biases in models highlight the need for robust regulatory frameworks to ensure its ethical and equitable use. Furthermore, the lack of training among Public Health professionals and the digital literacy of communities limit the potential impact of these technologies. This article examines the practical applications, ethical challenges, and strategies needed for the responsible adoption of AI in Public Health. It emphasizes the importance of training, interdisciplinary collaboration, and continuous research to ensure that AI becomes a transformative tool contributing to global well-being. If implemented ethically and sustainably, AI can play a crucial role in promoting equity and quality in Public Health systems.