AN ANALYTICAL STUDY OF CRIMINAL LIABILITY IN THE MEDICAL PROFESSION: DOCTORS AND HOSPITALS
AUTHOR – R. INDHU* & MS. SAYANA M**
* STUDENT AT VELS INSTITUTE OF SCIENCE, TECHNOLOGY & ADVANCED STUDIES (VISTAS)
** ASSISTANT PROFESSOR AT SCHOOL OF LAW, VELS INSTITUTE OF SCIENCE, TECHNOLOGY AND ADVANCED STUDIES (VISTAS)
BEST CITATION – R. INDHU & MS. SAYANA M, AN ANALYTICAL STUDY OF CRIMINAL LIABILITY IN THE MEDICAL PROFESSION: DOCTORS AND HOSPITALS, INDIAN JOURNAL OF LEGAL REVIEW (IJLR), 6 (7) OF 2026, PG. 285-293, APIS – 3920 – 0001 & ISSN – 2583-2344. DOI – https://doi.org/10.65393/IJLRV6I733
ABSTRACT
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.