AN ANALYTICAL STUDY OF CRIMINAL LIABILITY IN THE MEDICAL PROFESSION: DOCTORS AND HOSPITALS

Most of the AI systems rely on historical large datasets for predicting future trends and outcomes at a
pace which humans would not be able to match. The development of AI in India is in the initial stages
and there is no regulatory body focused solely on AI. Some of India’s state governments have also
taken few initiatives, such as establishment of Centre of Excellence for Data Science and Artificial
Intelligence by Karnataka, Safe and Ethical Artificial Intelligence Policy 2020 and Face Recognition
Attendance System by Tamil Nadu, AI-Powered System for monitoring driving behaviour by West
Bengal, AI System to fight agricultural risks by Maharashtra etc. As with any other technology, AI brings
with it a span of opportunities and challenges. In healthcare, AI could be beneficial in mining medical
records; designing treatment plans; forecasting health events; assisting repetitive jobs; doing online
consultations; assisting in clinical decision making; medication management; drug creation; making
healthier choices and decisions; and solving public health problems etc.
AI could be very helpful in areas where there is scarcity of human resources, such as rural and remote
areas. AI technology has been helpful in dealing with COVID-19 in India. It has helped in preliminary
screening of COVID-19 cases, containment of coronavirus, contact tracing, enforcing quarantine and
social distancing, tracking of suspects, tracking the pandemic, treatment and remote monitoring of
COVID-19 patients, vaccine and drug development etc. The path for adoption of AI driven healthcare
in India is filled with a lot of challenges. The unstructured data sets, interoperability issues, lack of open
sets of medical data, inadequate analytics solutions which could work with big data, limited funds,
inadequate infrastructure, lack of manpower skilled in AI, regulatory weaknesses, inadequate
framework and issues related to data protection are some of the key challenges for AI-driven
healthcare. To adopt AI-based healthcare, it is important to train workforce in AI so that they can
carefully handle sensitive health information, protect data against theft and use AI systems
effectively. It is also crucial that healthcare decisions based on AI solutions should have a rationale
and are explainable.