News

06 Aug 2025

On 6th August, 2025, we began this monthly series aiming to explore the transformative potential of AI for diversity in Southeast Asia's health systems. This webinar will take place on the first Wednesday of every month.

Dr. Karthik Adapa opened the session by discussing AI's potential to bridge health equity gaps and challenges like biased algorithms, data privacy, which this series will address.

Dr. Alain Labrique provided the keynote, focusing on how the Global South, specifically Southeast Asia, is leaping ahead with AI for health and the need to understand decision-making's role at this crossroads to shape the future of AI in health care. He shared the challenges and the WHO's framework for responsible AI. “Let’s ensure that AI becomes a force for equity, dignity, and better health for all.”

Regional perspective panel:

Dr. Chaminda Weerabaddana raised examples of low-risk AI to address human resource shortages and the quality of data. Considering these challenges, he urges that the potential focus should be on non-clinical applications in health care. “For AI to take a foothold in the system, we need better regulatory and governance mechanisms, explainable AI to build trust among providers and patients, and consciousness of biases since these models are not trained on our datasets.”

Dr Vinay Bothra raised alarms about early diagnosis and gave an example about the Cochrane collaboration on randomised control trials about too early or too much diagnosis, which gave us an over-gap between AI predictions and real-world outcomes. “Do we want quicker diagnosis, or do we want better outcomes? What’s our North Star?”

Ms. Sonam Yangchen spoke about how AI could support access to healthcare, improve supply chain management, and prevent NCDs through equity-based use cases in India and Tibet. “Building trust means ensuring AI systems are explainable in simple terms, auditable, and developed with public interest at the core.”

 Dr. Mona Duggal provided a country-level spotlight on India's AI strategy and developing landscape of digital health, from the governance level, adding significant relevance to India's AI mission to make “AI for All." “Most AI tools did not perform as expected in real-world settings… An FDA-approved American company backed out when sensitivity remained over 95% but specificity dropped to just 4% in Indian settings. This was an eye-opener about the importance of context-specific validation.”