Ethics of Artificial Intelligence and Big Data
TOPIC CLASSIFICATION
Subject: Ethics, Integrity, and Aptitude (GS Paper-IV)
Sub-topic: Ethics of AI and Big Data — Algorithmic Bias, Data Privacy, Autonomy, Accountability, Transparency, Ethical Governance of AI
Mains GS Paper-IV / GS Paper-III: Ethics of emerging technologies; data privacy; AI governance and regulation.
EXAMINER REASONING
AI ethics is a frontier topic for UPSC — it tests your ability to apply ethical principles (autonomy, justice, beneficence, non-maleficence) to rapidly evolving technologies. Prelims tests: key concepts (algorithmic bias, data privacy, right to be forgotten, data localisation), India's Digital Personal Data Protection Act (DPDPA) 2023, EU AI Act. Mains demands: (a) ethical principles for AI — transparency, accountability, fairness, explainability, (b) algorithmic bias — how AI systems discriminate (gender, race, caste), (c) data privacy vs. innovation — the ethical trade-off, (d) autonomous systems — who is responsible when an AI kills/harms? (trolley problem for autonomous vehicles, military drones), (e) India's regulatory approach — DPDPA 2023, National AI Strategy (AI for All), (f) job displacement — the ethics of technological unemployment, (g) AI and democracy — deepfakes, election manipulation, echo chambers. The examiner's favourite framing is: "How can India balance the benefits of AI with the ethical risks it poses?"
Core Concept
Ethical Principles for AI (from OECD, UNESCO, EU):
| Principle | Description | Example Issue |
|---|---|---|
| Transparency | AI systems should be explainable and their decision-making processes understandable | Black box problem — deep learning models whose decisions cannot be explained |
| Accountability | Designers and deployers of AI should be answerable for its outcomes | — who is liable when an autonomous car kills someone? |