Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?
Approach · directive: “introduce / how / do you perceive”
What it asks · Define AI briefly, show how it improves clinical diagnosis, and weigh the privacy risks of using health data, with a clear personal view.
The question has 3 parts — answer each
- Introduce the concept of Artificial Intelligence
- Explain how AI helps clinical diagnosis
- Give a clear view on whether AI in healthcare threatens individual privacy, with the safeguards needed
Open with · AI refers to machines that learn from data to perform tasks needing human intelligence, such as recognising patterns, predicting and deciding.
Cover
- Concept: machine-learning and deep-learning models are trained on large datasets and improve with more data, unlike fixed rule-based software.
- Diagnosis: reading X-rays, CT scans, retinal and pathology images, flagging TB, cancers and diabetic retinopathy early, and predicting risk from patient records.
- Reach and speed: decision support where specialists are scarce, faster triage and lower cost, a real gain for rural India.
- Privacy threat: yes. Health data is highly sensitive; breaches (the November 2022 attack on AIIMS Delhi's servers), re-identification and commercial misuse are real risks.
- Other concerns: informed consent, bias from unrepresentative data, unclear accountability for a wrong diagnosis and over-reliance on machines.
- Safeguards: the DPDP Act 2023, consent-based sharing under the Ayushman Bharat Digital Mission, ICMR's ethical guidelines for AI, anonymisation, audits and human review.
Close with · AI should assist the doctor, not replace her, and be adopted with strong consent, security and accountability norms.
Question: UPSC's CS (Main) 2023, GS Paper III — paper ↗. Approach: Minimalist IAS, checked 30 Sept 2026 (how we verify) — UPSC publishes no model answers. ·
Model answer · 211 words (UPSC limit 150) · Minimalist IAS
Artificial Intelligence refers to machines that learn from data to perform tasks needing human intelligence, such as recognising patterns, predicting and deciding; unlike fixed rule-based software, machine-learning and deep-learning models improve as they see more data.
AI in clinical diagnosis
- Imaging: models read X-rays, CT scans, retinal and pathology images to flag tuberculosis, cancers and diabetic retinopathy early, often before symptoms appear.
- Prediction: algorithms mine patient records to estimate the risk of complications and prompt timely intervention.
- Reach: decision support where specialists are scarce, faster triage and lower cost, a real gain for rural India.
Threat to privacy: yes, a real one
- Health data is the most sensitive personal data; the November 2022 attack on AIIMS Delhi's servers showed how exposed it is.
- Re-identification of anonymised datasets, commercial misuse by insurers or advertisers, and consent taken without understanding are live risks.
- Allied concerns: bias from unrepresentative training data, unclear accountability for a wrong diagnosis and over-reliance on the machine.
Safeguards
- The DPDP Act 2023 for consent and purpose limitation; consent-based sharing under the Ayushman Bharat Digital Mission; ICMR's ethical guidelines for AI in health; anonymisation, security audits and a doctor's final say.
AI should assist the clinician, not replace her, and be adopted only with firm consent, security and accountability norms.
Written by Minimalist IAS from facts checked at source (how we verify) — a little fuller than exam length, so every part of the question is covered; in the hall, keep the structure and trim the detail. UPSC publishes no model answers: compare your structure and coverage with this, then write your own.