Why in the news?
The Digital Ethics Centre at Delft University of Technology, Netherlands, has been designated as a WHO Collaborating Centre on AI for health governance.
What is artificial intelligence?
Artificial intelligence (AI) is a term applied to a machine or software and refers to its capability of simulating intelligent human behaviour, instantaneous calculations, problem-solving, and evaluation of new data based on previously assessed data.
The Potential of AI in Health Care
- Diagnosis and Treatment Planning: AI can analyze imaging (such as X-rays), help doctors identify diseases and plan treatment more effectively.
- Predictive Analytics: by analysing Electronic health records and other patient data AI can predict which patients are at risk of developing certain conditions.
- Clinical research and discovery: AI has enough potential to examine data on drug interactions and side effects, as well as to predict which compound will be the most effective in treating certain conditions.
- Robotic Surgery: AI-supported Robot surgeries will for sure minimize surgery-related complications and will assist doctors in precision-oriented tasks.
- Workforce optimization: AI can automate workflows and help extend scarce labour resources, reduce work fatigue and burnout, and enable operational and cost efficiencies. Also ,It can automate routine administrative tasks, like scheduling appointments and processing insurance claims. E.g. Virtual Assistants and Chatbots
- Healthcare supply chain resilience: Data-driven predictive models provide longitudinal visibility of supply along with real-time information regarding shortages and surpluses.
Concerns Associated with AI in Health Care
- Data Privacy and Security: The use of AI in healthcare demands huge amounts of patient data, which raises eyebrows about data privacy and security.
- Biasness: Biased result from such healthcare models is a possibility if they are not trained by data that represent a wider section of society. This may lead to inaccurate or unfair results, especially for marginalized sections of society.
- Lack of Transparency: The internal workings of the AI-based model are unknown to the user. Because of this property, AI models = “black boxes“, making them less trustable.
- Regulation and Governance: Lack of clear regulations and guidelines for the use of AI in healthcare. This raises concerns about who will take responsibility for any mistake made by AI-based systems (E.g. any mistake made by AI-based robotic surgeons).
- Other: Equitable use (in the initial phase there will be problems and complications for a lot of people), fear and anxiety of job loss, etc.
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Initiatives taken to integrate AI in the Current Healthcare Ecosystem
- Ayushman Bharat Digital Mission (ABDM): It provides a unique digital health ID for each citizen.
- Healthlocker/Personal Health Records (PHR): Digital national health database backed with a cloud-based storage system that serves as a single source of health data for the nation.
- National Health Stack (NHS): It includes the National Health Analytics Platform etc.
Guiding principals for the use of AI in healthcare (WHO)
- Protect autonomy.
- Ensure transparency, explainability and intelligibility.
- Foster responsibility and accountability.
- Ensure inclusiveness and equity.
- Promote human well-being, human safety and public interest.
- Promote AI that is responsive and sustainable.
Conclusion
AI technologies have the potential to improve diagnosis, treatment and health research. Further, it will ensure drug development, and public health functions like surveillance and outbreak response. To fully harness AI’s benefits, collaboration among stakeholders is essential for robust governance, ethical safeguards, and evidence-based policies. India must invest in both public and private organizations to support AI research in healthcare.