The Indian Council of Medical Research (ICMR) has drafted the country’s first ethical guidelines for the application of artificial intelligence (AI) in biomedical research and healthcare. The guidelines provide an ethical framework for the development of AI-based tools that benefit all stakeholders. AI for health relies heavily on data obtained from human participants, which raises concerns about potential biases, data handling, interpretation, autonomy, risk minimization, professional competence, data sharing, and confidentiality.
Guidelines for Ethical Principles in AI in Health
The guidelines are intended for all stakeholders involved in research on AI in healthcare, including creators, developers, technicians, researchers, clinicians, ethics committees, institutions, sponsors, and funding organizations. It includes separate sections addressing ethical principles for AI in health, guiding principles for stakeholders, the ethics review process, governance of AI for healthcare and research, and the informed consent process involving human participants and their data.
Potential Ethical Challenges in AI in Health
The adoption of AI technology in healthcare is growing in India. However, AI as a data-driven technology has many potential ethical challenges, which include algorithmic transparency and explainability, clarity on liability, accountability and oversight, and bias and discrimination, said ICMR Director General Dr Rajiv Behl.
Purpose and Development of the Guidelines
NTAGI Chief Dr N K Arora said the purpose of the guideline is to provide an ethical framework that can assist in the development, deployment, and adoption of AI-based solutions for biomedical research and healthcare delivery. The guideline has been formulated after extensive discussions with subject experts, researchers and ethicists, said Dr Arora.
Potential Benefits of AI in Health
The induction of AI into healthcare has the potential to be the solution for significant challenges like diagnosis and screening, therapeutics, preventive treatments, clinical decision-making, public health surveillance, complex data analysis, and predicting disease outcomes. This list is likely to grow in the future, the document said. The purpose of these guidelines is not to limit innovation or recommend any disease-specific diagnostic or therapeutic approach but to guide effective yet safe development, deployment and adoption of AI-based technologies in biomedical research and healthcare delivery, it said.