"It is therefore imperative to have an ethical framework that addresses issues specific to AI for biomedical research and healthcare," the guidelines stated.
The adoption of AI technology in healthcare is growing in India. However, AI as data-driven technology has many potential ethical challenges which include algorithmic transparency and explainability, clarity on liability, accountability and oversight, bias and discrimination, said ICMR Director General Dr Rajiv Behl.
"The DHR-ICMR AI Cell has identified the need to develop these guiding ethical principles concerning artificial intelligence and machine learning-based tools.
"These guidelines will provide the ethical framework for the development of AI-based tools which will benefit all stakeholders, including innovators, developers, patients, technologists, researchers, healthcare professionals, ethics committees, sponsors and funding agencies involved in research related to AI in biomedical research and healthcare," he said.
NTAGI chief Dr N K Arora said the purpose of the guideline is to provide an ethical framework which can assist in the development, deployment, and adoption of AI-based solutions for biomedical research and healthcare delivery.
The guidelines are intended for all stakeholders involved in research on artificial intelligence 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 artificial intelligence for healthcare and research, and the informed consent process involving human participants and their data.
The guideline has been formulated after extensive discussions with subject experts, researchers and ethicists, said Dr Arora.
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.
These guidelines will be used by experts and ethics committees reviewing research proposals involving the use of AI-based tools and technologies.
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