Policy Lab: AI and Healthcare /// December 2018

What are the current needs and gaps in the healthcare sector in India, and what role can AI play? What are the risks?

On December 3-4, Tandem Research brought together brought together multiple stakeholders from the healthcare ecosystem to identify knowledge and policy needs required to shape the trajectories of AI adoption in Indian health and medical systems.

AI applications, in addition to related technologies like big data and robotics, are expected to have transformational and disruptive possibilities within the healthcare sector across various verticals such as hospital management; diagnostics; pharmaceuticals; mental health and wellbeing; insurance; and predictive and preventive medicine.

With early identification of epidemics and pandemics possible, AI would enable a shift from reactive to preventive healthcare— streamlining health insurance claims and payouts, aiding mental health diagnosis and support, and even facilitating efficient drug discovery and formulation. In these terms, AI can be envisioned as pathway to the improvement of quality and accessibility in healthcare delivery and, thus, there is much investment and worldwide attention garnered towards AI adoption, especially in the technology and government spheres.

The potential positive impact is not without cost or concern, though. Lab participants contemplated the complexities of AI intervention in healthcare, including, but not limited to patient privacy and consent, data quality and gaps, algorithmic accountability and trust, the concentration of power and knowledge in the hands of private players and big-pharmaceutical corporations, and the misuse of patient information for surveillance. The consensus throughout the lab sessions pointed to the urgent need to examine these social, ethical, and governance-related challenges of AI adoption in healthcare. Because in order to steer the trajectory towards a future of net positivity for all of society, continuous deliberation is necessary to keep technologists and policy-makers on the track of AI for All.

  • Anil Misquith, Samihta Social Ventures / Aziz Premji University
  • Anukriti Chaudhari, iSpirit
  • Arun Sukumar, Observer Research Foundation
  • Champa Patel, Chatham House
  • Ding Wang, Microsoft Research
  • Ishani Pruthi, Dimagi India
  • John Nasuland, Harvard Medical School
  • Kachina Chawla, USAID
  • Mausumi Acharya, Chronix.Ai
  • Nimmi Rangaswamy, IIT Hyderabad
  • Oomen C. Kurian, Observer Research Foundation
  • Pattie Gonsalves, Sangath
  • Prabhat Lal, Grameen Foundation
  • Sujay Santra, iKure
  • Vidhusi Marda, Article 19


AI & Society