- Why in News- The Indian Council of Medical Research (ICMR) has released the country’s first ‘Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare’, aimed at creating “an ethics framework which can assist in the development, deployment, and adoption of AI based solutions” in the fields specified.
- The document, prepared by the Department of Health Research and the ICMR Artificial Intelligence Cell, Delhi, will be updated as and when the need arises.
- As per the guidelines, the ethical review process for artificial intelligence in health comes under the domain of the ethics committee. The document notes that the regulation of AI technologies in healthcare is still in its nascent stage even in developed countries.
Indian Council of Medical Research (ICMR) in the document outlines 10 key patient-centric ethical principles for Artificial Intelligence (AI) application in the health sector.
What are the 10 Guiding Principles?
- Accountability and Liability Principle: It underlines the importance of regular internal and external audits to ensure optimum functioning of AI systems which must be made available to the public.
- Autonomy Principle: It ensures human oversight of the functioning and performance of the AI system. Before initiating any process, it is also critical to attain consent of the patient who must also be informed of the physical, psychological and social risks involved.
- Data Privacy Principle: It mandates AI-based technology should ensure privacy and personal data protection at all stages of development and deployment.
- Collaboration Principle: This principle encourages interdisciplinary, international collaboration and assistance involving different stakeholders.
- Safety and Risk Minimization Principle: This principle aimed at preventing “unintended or deliberate misuse”, and a favorable benefit-risk assessment by an ethical committee among a host of other areas.
- Accessibility, Equity and Inclusiveness Principle: This acknowledge that the deployment of AI technology assumes widespread availability of appropriate infrastructure and thus aims to bridge the digital divide.
- Data Optimization: Poor data quality, inappropriate and inadequate data representations may lead to biases, discrimination and errors.
- Non-Discrimination and Fairness Principles: In order to refrain from biases and inaccuracies in the algorithms and ensure quality AI technologies should be designed for universal usage.
- Trustworthiness: Need to have a simple, systematic and trustworthy
way to test the validity and reliability of AI technologies.
- India has a host of frameworks which marry technological advances with healthcare. These include
- the Digital Health Authority for leveraging Digital health Technologies under the National Health Policy (2017),
- the Digital Information Security in Healthcare Act (DISHA) 2018 and
- the Medical Device Rules, 2017.
- AI cannot be held accountable for the decisions it makes, so an ethically sound policy framework is essential to guide the AI technologies development and its application in healthcare.
Further, as AI technologies get further developed and applied in clinical decision making, it is important to have processes that discuss accountability in case of errors for safeguarding and protection.
