Artificial intelligence (AI) has evolved considerably in the last 60 years. While many AI applications have been deployed in high-income country contexts, use in resource-poor settings remains relatively nascent. With a few notable exceptions, limited examples of AI are being used in such settings. However, there are signs that this is changing. Several high-profile meetings have been convened in recent years to discuss developing and deploying AI applications to reduce poverty and deliver a broad range of critical public services. 

At the GPAI Summit 2023, a session on AI and Global Health- Role of AI in advancing healthcare was organized. The speakers include Dr Ricardo Baptista Leite, CEO of i-DAIR; Mr Sameer Kanwar, Director Digital Health, India and South Asia, PATH; Mr Girish Raghavan, VP Engineering, GE, Healthcare; Dr Geeta Manjunath, Founder, Nirmai; Mr Kiran Anandampllai, Founder & CEO, i-Drishti; Dr Karti Adapa. Regional Advisor- Digital Health, WHO, South East Asia, Regional Office, Government of India; Dr Vinod Paul, AIMS.

During the session, the panelists spoke about various topics, including the role of AI in medical research and the ethical concerns of AI in healthcare. According to Sameer Kanwar, working with AI for one year is enough to know god. In his opinion, the post-COVID era in India brought together the public and private sectors. Presently, India's health sector is placed very well.

Implementation of AI models

AI models will seem very efficient at a proof of concept stage. However, the actual capacity of the model can only be estimated after its successful implementation. To understand how this process can be carried out with ease, the panelists pointed out means to apply AI tools in a sensitive sector such as healthcare:

• The developers should put themselves in the shoes of the users.
• The developers should work with the doctors to understand the use cases of the model and make alterations to the functioning accordingly.
• Clear validation of how to train the model and the authenticity of training data should be ensured.
• The initial developments should be directed towards how great the result would be
• The prospect of the study should be clear: The developers should be responsible enough to trust the result produced by the model.
• Behind the model should be a team of diverse experts.
• The developers should ensure that the AI is human-centric
• GenAI and Universal Health Coverage (UHC)

With the advent of AI, UHC has improved drastically. For instance, telemedicine can aid a community worker in rural India to make the initial diagnosis. It has helped improve the application of technology, integrating technology and problem-solving with recording. 

According to Dr. Ricardo, the world has set a milestone to achieve a UHC goal by 2030. But he opines that the government alone can not do this. They need the help of the private sector. Richer countries have developed broken AI systems, and these are exported to lower-income countries.

The world must ensure that lower and middle-income countries have the resources to handle these AI technologies. If not, the rich will get richer, the poor will get poorer, and people in lower and middle-income countries will get sicker.

We need great models that are inclusive and don't leave anyone behind. Dr. Ricardo applauded India for taking the lead in the transformation of AI in healthcare.

India's destiny

AI is forcing change in the healthcare sector in a disruptive manner. India, as a nation, has the power to excel in AI. According to Vinod K Paul, "It is India's destiny to be a leader in digital health".

Successful Indian initiatives, including Cowin and Aasyushman's mission, are evidence that we can lead nations across the globe in healthcare.