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The double-edged algorithm: A rapid review exploring the trustworthy and responsible use of generative AI in public health
3
Zitationen
3
Autoren
2025
Jahr
Abstract
Objective: Generative artificial intelligence (genAI) technologies have rapidly evolved, offering potential to strengthen core public health functions such as health communication, surveillance, and emergency preparedness. While genAI may enhance public health outcomes by enabling tailored messaging, helping to combat misinformation, and supporting data-driven decision-making, its integration raises significant concerns about equity, privacy, and trust. Methods: This rapid review explores guiding principles for the trustworthy and responsible use of genAI in public health contexts. Following established rapid review protocols, peer-reviewed and grey literature published since 2014 were identified and analyzed thematically. Results: Ten articles met the inclusion criteria, focusing on genAI applications across various public health settings. Ten themes were generated that describe guiding principles for the trustworthy and responsible use of genAI in public health. The themes emphasize the importance of human oversight, transparency, equity, accountability, and culturally relevant communication. While genAI can be used to support health behavior change, enhance health communication across literacy levels, and promote community engagement, risks such as algorithmic bias, data misuse, and the amplification of health disinformation must be mitigated. Conclusion: Organizational policies must reflect ethical considerations and address current regulatory gaps to help mitigate these risks. Workforce training, interdisciplinary collaboration, and policy development are vital to support responsible and trustworthy implementation. This review provides preliminary insights that can help public health organizations begin to consider guidling principles for policies for guiding genAI adoption and use, emphasizing the importance of human-centered and ethically grounded approaches. Findings also identify future research needs, including the evaluation of genAI tools in diverse public health contexts, assessment of real-world impacts, and exploration of governance frameworks. This review offers an initial foundation for public health organizations to consider potential applications of genAI and develop policies that support its responsible and trustworthy use.
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