Transformative potential of artificial intelligence in US CDC HIV interventions: balancing innovation with health privacy.

Abstract

Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment through the application of advanced technologies such as machine learning (ML), deep learning (DL), and generative AI (Gen AI). These technologies can enhance the monitoring, management, and analysis of vast and complex HIV-related datasets, enabling more timely predictions of potential risks and improving HIV care strategies. AI is poised to streamline HIV prevention interventions by increasing workforce efficiency, supporting expanded accessibility and sustainability of preexposure prophylaxis (PrEP) care in nontraditional settings, and supporting clinical decision-making. Additionally, when utilized within HIV care systems, AI can help close gaps in diagnosis, treatment, and continuous care engagement. However, to optimize AI's potential in HIV prevention, careful implementation is crucial. Challenges such as reducing bias, ensuring ethical standards (including health privacy standards) are maintained, and mitigating risks like AI hallucinations must be addressed. Thoughtful integration, community consultation, and continuous evaluation will be critical to ensuring that AI plays a beneficial role in HIV prevention and drives innovations that lead to more equitable health outcomes. This editorial review explores AI's transformative potential, focusing on the US CDC's key public health strategies for HIV prevention. When aligning with public health strategies - particularly in countries supported by initiatives like President's Emergency Plan for AIDS Relief (PEPFAR) - AI can contribute significantly to global efforts to end the HIV epidemic. It offers a vision for AI's future application in HIV prevention, emphasizing the need for a holistic and syndemic approach to improving HIV prevention worldwide.