Reimagining artificial intelligence in community medicine: From promise to equitable implementation

Abstract

Sir, We read with great interest the Editorial by Chugh and Ravichandran.[1] The authors[1] rightly highlight that artificial intelligence [AI] can augment surveillance, risk stratification and decision support in primary care settings. However, evolving global evidence suggests that the ‘future’ envisioned for AI in community medicine will be determined less by algorithmic sophistication and more by how well equity, ethics and implementation science are embedded into health system design.[2-4] In this context, we wish to offer a constructive, solution-oriented perspective that may be relevant not only for India but also for other low- and middle-income countries (LMICs).[5] First, the current discourse on AI in community medicine often underestimates health inequities. AI tools deployed in primary care can inadvertently magnify existing inequities when trained on non-representative data or implemented in digitally excluded populations.[2] AI-driven public health tools are disproportionately piloted in the well-resourced settings, with limited external validation in rural and peri-urban communities where the burden of disease is highest.[3] Further, recent work argues that AI policy in public health must move beyond generic optimism towards explicit governance frameworks. A structured agenda has been proposed for policymakers that foregrounds transparency, accountability, data-governance safeguards and participatory design involving communities and civil society.[4] In an Indian public health context, it has been proposed that AI initiatives must be integrated into existing health system functions such as surveillance, health promotion and primary care rather than being implemented as stand-alone ‘pilot projects’.[5] In contrast, much of the AI narrative in community medicine still focuses on lists of potential applications – chatbots, risk calculators and predictive dashboards – without specifying how these tools will be governed, evaluated and de-implemented if they prove harmful or inequitable.[1,4,5] Third, there is now a growing emphasis on ‘equity by design’ and digital divide mitigation in AI-enabled health interventions. AI is a potential catalyst for health equity in primary care only when digital infrastructure gaps, affordability, connectivity and human resource training are addressed in parallel.[6] ‘Equity by design’ principles for digital health, ranging from inclusive needs assessment and co-design with marginalised groups to transparent communication of model limitations and participatory evaluation have been proposed.[7] These developments suggest that community medicine curricula and programmes must move from viewing AI as a neutral technology to treating it as a socio-technical intervention that can either narrow or widen inequities, depending on how it is designed and governed. Drawing on these insights, we propose a six-pillar framework for AI-ready community medicine in LMICs, namely: (i) problem-first, not technology-first;[3-5] (ii) context-specific data governance;[4,8] (iii) equity by design;[2,6,7] (iv) implementation science and iterative evaluation;[3-5,8] (v) workforce capacity-building;[3-5,9] and (vi) ethical and generative-AI preparedness.[4,8,9] Positioned against this backdrop, the editorial by Chugh and Ravichandran[1] provides a timely entry point and also highlights an opportunity to shape the global conversation on AI in community health. In conclusion, AI in community medicine should be framed not only as a technological innovation but as a public health reform agenda centred on equity, ethics and system resilience. By encouraging submissions that present rigorous, context-sensitive and ethically grounded AI work, the editorial can play a pivotal role in demonstrating how LMICs can move from aspirational rhetoric to measurable improvements in population health, thereby providing the lessons of global relevance. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest. Use of artificial intelligence (AI)-assisted technology for manuscript preparation The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the preparation of the manuscript and no images were manipulated using AI.

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