Rethinking Reproductive Healthcare with AI

Abstract

Artificial intelligence (AI) has been recognized by the World Health Organization for its transformative potential in addressing global reproductive healthcare challenges, including inequitable access to monitoring and treatment and limited diagnostic precision. AI offers significant promise in enhancing diagnostic accuracy enabling data-driven decision-making for personalized preventive and therapeutic interventions. However, its deployment also raises ethical and operational concerns, such as data privacy risks, algorithmic bias, legal complexities, cultural sensitivity, overreliance on AI-generated recommendations, and the potential deskilling of clinicians. Addressing these challenges requires inclusive frameworks for responsible integration. Moreover, AI-driven digital transformation must align with the broader call for sustainable innovation outlined in the United Nations’ 2030 Agenda and European Union regulations defining the requirement for safe and secure integration standards. This research explores pathways for responsible and sustainable AI adoption in reproductive healthcare while mitigating associated risks. It introduces the (H)iCARE framework, which advocates for (1) human-centric hybrid models that integrate AI-driven innovations with clinical expertise to ensure balanced innovations. The framework also (2) embraces a broader, humanity-oriented perspective to ensure inclusivity beyond a limited subset of stakeholders, and (3) fosters a learning-driven approach that prioritizes continuous skill development to prevent cognitive complacency. While developed in the context of reproductive healthcare, its principles extend across the healthcare sector, providing a foundation for AI-integrated information system design and a roadmap for ethical, sustainable advancements, additionally fostering discussion on future research priorities.