APSC CCE Mains PYQ Solved | APSC CCE 2023 Model Answer

Preparing for the APSC CCE Mains Examination requires much more than just reading books and making notes. One of the most effective ways to understand the actual demand of the examination is by practicing and analyzing Previous Year Questions (PYQs).

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APSC Mains GS Paper 2: 2023: “The increasing use of artificial intelligence (AI) is expected to fundamentally transform the ways in which governance is done in India.” Discuss the challenges to be faced in this regard. (15 Marks, 250 words)

Model Answer:

Guided by NITI Aayog’s “AI for All” strategy and the ₹10,300 crore IndiaAI Mission, Artificial Intelligence is poised to shift India’s governance paradigm from reactive administration to predictive, human-centric service delivery.

Transformative Potential in Governance (Context)

Targeted Service Delivery: Integration of AI with Digital Public Infrastructure (Aadhaar, UPI) and tools like Bhashini enhances multilingual accessibility.
Predictive Administration: Transitioning from post-disaster response to early warning.
- Assam Example: Under Mission Mausam, the Central Water Commission (CWC) has deployed AI/ML models across 8 stations in the Brahmaputra basin to provide precise, 24-hour flood forecasts.

Key Challenges in AI-Driven Governance

1. Data Privacy and Cybersecurity Risks

Surveillance vs. Privacy: Massive mining of citizen data raises concerns regarding mass surveillance and violation of the fundamental right to privacy (Puttaswamy Judgment).
Vulnerability: Centralized government data repositories face severe ransomware and cyber-attack threats (e.g., the AIIMS Delhi cyberattack).

2. Algorithmic Bias and the Digital Divide

Exclusion Errors: AI models are largely trained on urban-centric datasets. Deploying them can marginalize rural and tribal populations, particularly in regions like North-East India.
Infrastructure Deficit: While the IndiaAI Mission plans to deploy 38,000 GPUs, the lack of last-mile digital connectivity and edge-computing in rural India (as highlighted by NSSO & TRAI data) remains a massive bottleneck.

3. Ethical and Regulatory Void

The “Black Box” Dilemma: Machine learning algorithms lack transparency. If an AI denies a citizen access to a PDS ration or welfare scheme, establishing accountability becomes administratively complex.
Misinformation: As noted in the WEF Global Risks Report, AI-generated deepfakes pose a severe threat to electoral integrity and social harmony.
Lack of Comprehensive Law: India currently relies on the DPDP Act, 2023 and IT Rules, but lacks a dedicated statutory framework to regulate AI ethics, liability, and Intellectual Property rights.

4. Administrative and Capacity Bottlenecks

Skilling Deficit: There is a severe dearth of specialized AI professionals within the bureaucracy to independently audit, deploy, and monitor algorithmic decisions.

To realize the vision of Viksit Bharat 2047, India must anchor its digital transition in constitutional values, evolving a robust framework for “Responsible AI” that ensures inclusive growth and fulfills SDG 16 (Strong Institutions).

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