AI for Healthcare: Insights from India
Report
/
Aug 2020

AI for Healthcare: Insights from India

Urvashi Aneja /Claire Muñoz Parry

In this paper, we collaborated with researchers at Chatham House, UK, to identify the opportunities, challenges, and risks of the use of AI for healthcare. The India section of this report is based on a workshop that brought together experts in ICT4D, AI, healthcare, public policy, along with AI companies, supported by Friedrich-Ebert-Stiftung.

AI, the use of coded computer software routines with specific instructions to perform tasks for which a human brain is considered necessary, is providing the healthcare sector with new advances that are being hailed as game changers.

The risk and challenges of integrating AI into healthcare are closely related to the use of the data needed to feed AI systems. Issues around quality, safety, governance, privacy, consent, and ownership must all be properly addressed. A lack of explainability, as it is almost impossible to understand how AI arrived at a specific decision, also points to a potential lack of trust in AI systems.

India provides a case study of how a country is actively promoting the use of AI to address healthcare needs. However, the deployment of AI in India is still at a very nascent stage, particularly for clinical interventions.

The challenge of delivering quality healthcare at scale presents a strong case for developing AI-based solutions for healthcare in India. However, a complex health landscape involving numerous stakeholders, competing priorities, entrenched incentive systems, and institutional cultures gives rise to a range of challenges and risks across the stages of development, adoption and deployment.

The quality of digital infrastructure, affordability, and variable capacity among states and medical professionals are together likely to result in the adoption of AI applications primarily by India’s well-established private hospitals. This in turn could result in new inequities in access to quality healthcare.

The effectiveness of AI systems will depend on accurate problem identification and solution matching. Currently, there is a risk that solutions are being technology-led rather than problem-led, and as a result are often blind to particular contextual needs or constraints.

This report was authored by the team at Tandem Research, the former home of the Responsible Technology Initiative. The workshop on AI and Healthcare was a part organised in partnership with Friedrich-Ebert-Stiftung.