Q. Introduce the concept of Artificial Intelligence (Al). How does Al help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of Al in healthcare?

Model Answer: 

Artificial Intelligence (AI) refers to the simulation of human cognitive functions—such as learning, reasoning, and pattern recognition—by computer systems.

1. AI in Clinical Diagnosis

• Medical Imaging: Analyzes MRIs/X-rays rapidly with superior precision (Google DeepMind for diabetic retinopathy).
• Predictive Diagnostics: Machine learning predicts disease onset using patient history and genetics (IBM Watson in oncology).
• Early Detection: Identifies subtle anomalies in ECGs/scans before clinical symptoms visibly manifest.
• Pathology Automation: Rapidly processes blood and tissue samples, minimizing human error and diagnostic turnaround time.

2. Privacy Threats of AI in Healthcare

• Data Breaches: Centralized AI training datasets are lucrative targets for cyberattacks, exposing sensitive health records.
• Unauthorized Profiling: AI can deduce unshared medical conditions, enabling potential discrimination by employers or health insurers.
• Consent Violations: Secondary use of patient data for algorithm training often occurs without explicit, informed consent.
• De-anonymization Risks: Advanced AI can easily re-identify “anonymized” patient data by cross-referencing multiple digital footprints.

Balancing AI’s clinical benefits requires enforcing the Digital Personal Data Protection (DPDP) Act 2023 and ICMR Guidelines, strictly safeguarding data privacy as a fundamental right (Puttaswamy judgment).