UPSC Essentials | Mains Answer Practice | GS 2 : Questions on India–EU FTA negotiations and AI in law enforcement (Week 136)

UPSC Essentials brings to you its initiative for the practice of Mains answer writing. It covers essential topics of static and dynamic parts of the UPSC Civil Services syllabus covered under various GS papers. This answer-writing practice is designed to help you as a value addition to your UPSC CSE Mains. Attempt today’s answer writing on questions related to topics of GS-2 to check your progress.

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Discuss the role of free trade agreement (FTA) negotiations between India and the European Union in addressing non-tariff barriers like carbon taxes.

Discuss the benefits and risks of deploying Artificial Intelligence (AI) in law enforcement in India.

Relevance: This question links GS-II (International Relations) with climate diplomacy and trade governance, highlighting how emerging non-tariff barriers like CBAM reshape India’s export strategy and negotiating leverage in modern FTAs.

Note: This is not a model UPSC answer. It only provides you with thought process which you may incorporate into the answers.

— From January 1, Indian steel and aluminium exports to Europe started facing higher costs and narrower margins. Under the Carbon Border Adjustment Mechanism (CBAM), the EU charges imports based on the carbon emissions produced during production.

— The new tax might wipe off 16-22% of actual prices paid, compel contract renegotiations, and decrease Indian product presence in the EU, a market that absorbs approximately 22% of India’s steel and aluminium exports.

— CBAM extends the EU’s carbon pricing system to imports. In Europe, companies pay for their emissions under the EU Emissions Trading System. CBAM imposes a similar cost on foreign producers to prevent companies from shifting production to countries with weaker climate rules. It covers steel, aluminium, cement, fertilisers, electricity, and hydrogen, with more sectors likely to be added over time. The UK also plans to introduce a similar system.

— By harmonising standards, expediting customs, recognising certifications, and resolving regulatory obstacles like the EU’s Carbon Border Adjustment Mechanism (CBAM), which will lower costs and complexity for Indian exporters in industries like textiles, pharmaceuticals, and food, the India-EU Free Trade Agreement (FTA) negotiations are essential for addressing non-tariff barriers (NTBs) and promote more equitable market access beyond tariffs.

— By concentrating on technical trade barriers (TBTs), sanitary and phytosanitary (SPS) measures, and origin rules, the FTA aims to streamline procedures, guarantee regulatory cooperation, and integrate digital trade, making trade easier and more competitive for both parties.

— It aims to streamline customs paperwork and procedures, lowering red tape and improving logistics for Indian exporters.

— By improving overall market access, the FTA strengthens the position of Indian exporters in the EU and vice versa for EU companies in India.

— India must find a resolution for CBAM under the ongoing FTA negotiation with the EU. Domestically, India should strengthen carbon accounting frameworks and support cleaner production.

India-Africa digital partnership is achieving mutual respect, co-development and long-term institutional partnerships. Elaborate. (2025)

‘Indian diaspora has a decisive role to play in the politics and economy of America and European Countries’. Comment with examples. (2020)

Relevance: This question is important for GS-II (Polity & Governance) as it examines the impact of emerging technologies on internal security, rule of law, and the protection of fundamental rights. It also tests understanding of ethical governance, privacy (Article 21), and state accountability in the use of AI-driven policing tools.

Maharashtra chief minister Devendra Fadnavis (left) and Microsoft Chairman and CEO Satya Nadella (right). (Express photo)

— A predictive artificial intelligence (AI) tool called MahaCrimeOS AI, built with support from Microsoft, is assisting Maharashtra Police in investigations. As generative AI takes off, India’s law enforcement architecture is keenly exploring the technology.

— For police forces, the appeal of AI lies in its promise to process vast amounts of data faster than human investigators.

— AI systems can sift through call records, CCTV feeds, financial trails and digital evidence to spot patterns, link cases and flag suspects in real time, helping stretched forces manage rising workloads.

— In India, where cybercrime and online fraud are growing rapidly and police resources remain uneven across states, officials see AI as a way to boost efficiency, improve response times and modernise policing without large increases in manpower.

— It can help investigators link cases, analyse digital evidence, and respond to threats faster and more effectively.

— According to CyberEye’s website, its CrimeOS AI offers what it calls an end-to-end investigation workflow. This includes the ability to ingest PDFs, images, videos, handwritten notes across several regional languages to “auto-generate” cases and identify initial threat vectors.

— The AI also suggests investigation paths along with standard operating procedures and suggested tactics, techniques and procedures to follow. It can also generate legal notices and analyse responses sent by telecom companies.

— AI-driven policing risks deepening existing biases in law enforcement. Because such systems rely heavily on historical police data, they can reinforce patterns of over-policing and lead to unfair targeting of certain communities.

— Concerns also persist around accuracy, transparency and the absence of clear legal safeguards.

— In India, broad exemptions for law enforcement under data protection laws further complicate accountability, even as AI-enabled tools like facial recognition become more widespread and intrusive in public spaces.

— However, predictive policing has raised serious concerns of unfair targeting, wrongful suspicion, and increased surveillance of specific groups. There are also concerns around transparency, accuracy, data quality and the lack of clear laws governing how AI decisions are made or challenged.

How can AI improve accuracy and transparency in governance?

e-governance projects have a built-in bias towards technology and back-end integration than user-centric designs. Examine. (2025)

e-governance, as a critical tool of governance, has ushered in effectiveness, transparency and accountability in governments. What inadequacies hamper the enhancement of these features? (2023)