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ICMR’s ETHICAL PRINCIPLES FOR AI IN HEALTHCARE 
ICMR’s ETHICAL PRINCIPLES FOR AI IN HEALTHCARE 

December 17, 2024

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SUMMARY

India's healthcare system faces significant challenges due to its large population, a shortage of healthcare professionals, increasing costs, and systemic inequalities. However, it stands to gain immensely from advancements in AI and machine learning technologies. These technologies can improve decision-making in various areas, including diagnosis, medical imaging, health management, and predicting disease outbreaks. Given that AI operates in sensitive fields like healthcare, it is essential to have human oversight to ensure safety and accountability. The Indian Council of Medical Research (ICMR) has established ethical guidelines for the responsible development, validation, and deployment of AI in healthcare, focusing on autonomy, data privacy, equity, collaboration, and trustworthiness. 

AI applications in healthcare, such as predicting diagnoses, providing mental health support through chatbots, and managing clinic and hospital operations, have the potential to enhance patient outcomes and improve healthcare efficiency. Nevertheless, it is vital to implement these technologies cautiously, adhering to ethical principles and ICMR guidelines to tackle challenges like over-reliance on technology, biases, and data security. By following these guidelines, AI can be seamlessly integrated into India's healthcare system, improving accessibility and equity while maintaining the crucial human element in medicine. 

INTRODUCTION

A highly populous country like India requires modernized solutions in the healthcare industry to overcome potential problems such as a shortage of qualified healthcare professionals, rising healthcare costs, and inequality in healthcare systems. AI/ML technologies will improve decision-making in diagnosis, screening, medical imaging, health management, drug discovery, public health surveillance, and disease outbreak prediction, as noted by the Indian Council of Medical Research (ICMR). 

 AI is data-driven technology, where computer systems are trained on an infinite amount of data to make predictions based on algorithms. AI has the potential to work unsupervised, but ICMR is guiding technologists to develop human-monitored AI (Human in The Loop) technology for medical use because of its direct impact on people's health. Additionally, AI cannot be held accountable for its decisions, so humans should be the final decision-makers on AI healthcare products. 

As healthcare and biomedical research are sensitive areas, the DHR-ICMR artificial intelligence cell has formulated a set of patient-centric guidelines for developing, validating, and deploying AI in healthcare and research. The guidelines apply to stakeholders, innovators, developers, technologists, researchers, healthcare professionals, ethics committees (ECs), institutions, sponsors, and funding organizations attempting to incorporate artificial intelligence into healthcare and biomedical research. 

ICMR’S ETHICAL PRINCIPLES FOR AI TECHNOLOGY IN HEALTHCARE 

  1. Autonomy: The patient or participant must be fully informed about the AI technology before including it and has the full right to choose or reject the AI technology. 
  2. Data Privacy: Human medical data used to train the AI model should be properly anonymized, and consent must be obtained for excess data storage and data sharing. Data maintenance and sharing should fall under the standards of DISHA and PDP guidelines and ensure patient privacy. 
  3. Optimization of Data Quality: The accuracy of AI is directly proportional to the amount and quality of data used for training. Therefore, the manufacturer must ensure that the training data is unbiased and includes data from vulnerable populations and smaller communities. 
  4. Collaboration: The development of AI technology in healthcare is an interdisciplinary endeavor, so the team must have healthcare experts in all phases of development and deployment. The details of the collaboration regarding data collection and sharing must be approved by the Health Ministry’s Screening Committee (HMSC) before commencement. 
  5. Security and risk minimization: Human biometric and medical data are vulnerable to cyberattacks, so they need to be protected from global technology by proper anonymization. The security standards must be raised to real-time standards to ensure patient data protection. The risk minimization principle advises stakeholders to regularly conduct external audits and submit the documents to the supervisory authorities. 
  6. Trustworthiness: AI-based solutions must be reliable, valid, and transparent, with well-documented, explainable results, to gain trust among physicians and participants. 
  7. Accessibility, equity, and inclusiveness: The developers and authorities must consider disadvantaged populations, language barriers, poor infrastructure, and our country's economic status and ensure that AI technology is available in all local languages and that in an environment with low resources, the technology works to be made equally accessible to all. 
  8. Non-discrimination and fairness principles: This principle ensures that the developed AI technology is intended for universal use and that an end-user feedback analysis is continuously carried out to minimize inaccuracies and biases. 
  9. Accountability and Liability: Organizations need to define their legal responsibilities before adopting AI technology for clinical use. 
  10. Validity: AI technologies must undergo rigorous clinical and field validation before deployment to ensure their safety and effectiveness. 

APPLICATIONS AND BENEFITS OF AI IN HEALTHCARE: 

  1. Implementing AI technology in the healthcare system to predict diagnoses and read medical images would reduce human diagnostic error and thus increase the chances that patients will be treated for it.  
  2. With the introduction of AI-powered interactive chatbots, psychiatric patients can receive support to improve their behavior and mental health when they are reluctant to attend face-to-face consultations. 
  3. Clinics and hospitals can be easily managed through the use of AI technologies at different levels, which would increase productivity. 

CONCLUSION 

Although medical AI has many benefits, over-reliance on AI technologies negatively impacts the doctor-patient relationship. Physicians should not only rely on AI technologies in their practice but also be aware of all other modalities in which they treat patients. 

Medical AI has enormous potential to overcome some of the major challenges in healthcare, such as the lack of medical professionals and infrastructure, rising healthcare costs, and difficulties in the implementation of new technology due to the complex healthcare system. AI technologies in healthcare are major inventions and need to be applied cautiously and slowly with utmost care in various medical fields, and people should control and design them according to the needs of the field by following the ICMR guidelines. 


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ICMR’s ETHICAL PRINCIPLES FOR AI IN HEALTHCARE.pdf

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