Recently, a span of a 40-year-old bridge collapsed in Vadodara, Gujarat, on July 9, sending multiple vehicles into the Mahisagar river and resulting in the death of 18 people.
What causes recurring public infrastructure failures in India?
Ageing and outdated infrastructure: Many structures like the Morbi suspension bridge (2022) in Gujarat had exceeded their intended lifespan, yet continued to be in use without adequate upgrades.
Overuse and overload beyond design capacity: Bridges and roads originally designed for lower traffic volumes now face high urban and industrial load, as seen in the Indrayani pedestrian bridge collapse in Pune (2024) due to overloading.
Neglect and poor maintenance: Lack of routine inspections and maintenance led to incidents like the Vadodara bridge collapse (2024), where locals had raised concerns that were ignored by authorities.
Institutional inefficiency and under-resourcing: Municipal and local bodies often remain understaffed and underfunded, unable to monitor and maintain growing infrastructure needs, especially in peri-urban areas.
Lack of accountability and transparency: Even after fatal accidents like the Mizoram railway bridge girder collapse (2023), failure analysis reports are rarely made public, limiting systemic learning and corrective action.
What is Peri-urban infrastructure?
Peri-urban infrastructure refers to the basic facilities and services (like roads, bridges, water supply, drainage, electricity, etc.) found in the transitional zones between urban and rural areas.
Why is peri-urban infrastructure more prone to collapse?
Unregulated and informal urban expansion: Peri-urban areas often develop without proper zoning laws, building codes, or infrastructure planning. This results in substandard construction, making infrastructure vulnerable to collapse. In many Indian outskirts, flyovers and water systems are built around unplanned colonies, lacking load assessment.
Jurisdictional ambiguity and poor coordination: Peri-urban regions often fall between urban and rural governance structures, leading to confusion in responsibility for maintenance and oversight. In Delhi NCR’s fringes, conflicts between municipal bodies and panchayats delay repair and auditing of key infrastructure.
Low visibility and weak political prioritization: These areas lack media attention and political pressure seen in core urban centres, resulting in deferred maintenance. In Hyderabad’s outer zones, repeated complaints about weakening culverts were ignored until seasonal floodingcaused failure.
How can AMRUT and UIDF improve asset upkeep?
Focused maintenance and retrofitting: AMRUT 2.0 prioritizes the retrofitting of old urban infrastructure such as pipelines, water supply, and sewerage systems. Eg: In cities like Agra and Pune, AMRUT funding has helped upgrade outdated drainage systems to prevent floodingand infrastructure degradation.
Targeted financial support for smaller cities: UIDF provides low-cost loans to Tier-2 and Tier-3 cities that often lack budgetary resources for upkeep. Eg: In peri-urban areas of Madhya Pradesh, UIDF enabled the repair of worn-out roads and bridges strained by rapid population growth.
Promotion of digital monitoring and audits: Both schemes encourage the use of geo-tagging and digital tracking tools to monitor asset health and schedule timely repairs. Eg: Cities like Bhubaneswar and Surat use AMRUT-linked dashboards to track infrastructure health and flag issues before failures occur.
What gaps delay audits and accountability post-collapse?
Jurisdictional overlap between agencies: Multiple departments—urban development, public works, and local bodies—often share responsibility for infrastructure. This leads to confusion over which authority must initiate audits after a collapse. Eg: After a flyover collapse in Hyderabad, delays occurred as both the GHMC and state PWD passed the responsibility to each other.
Political interference and blame-shifting: In high-profile accidents, inquiries are sometimes delayed or diluted due to political pressures or attempts to shield influential contractors. Eg: In the Kolkata Vivekananda flyover collapse (2016), early accusations were politicized, stalling a clear and prompt audit process.
Way forward:
Establish a unified statutory audit authority: Create a dedicated, independent body responsible for conducting post-collapse audits across all public infrastructure, ensuring timely investigations, clear jurisdiction, and mandatory public disclosure of findings.
Implement real-time digital monitoring systems: Use GIS mapping, IoT sensors, and AI-based predictive maintenance tools to track structural health and alert authorities proactively, minimizing risks and improving accountability.
Mains PYQ:
[UPSC 2014] Explain how Private Public Partnership arrangements, in long gestation infrastructure projects, can transfer unsustainable liabilities to the future. What arrangements need to be put in place to ensure that successive generations’capacities are not compromised?
Linkage: The article highlights several incidents of catastrophic public infrastructure failures in India, such as a 40-year-old bridge collapse in Vadodara, a pedestrian bridge collapse in Pune, and a metro pillar collapse in Bengaluru. This PYQ is highly relevant as it directly addresses the critical themes of long-term infrastructure management, potential liabilities, and ensuring future capacity.
Recently, the Supreme Court of India has intervened in the ongoing Special Intensive Revision (SIR) of electoral rolls in Bihar, urging the Election Commission (EC) to consider documents like Aadhaar, EPIC, and ration cards as valid identity proof.
Why did the SC question Aadhaar’s exclusion from voter ID documents?
Widespread Use for Identity Verification: The Court noted that Aadhaar is one of the most widely used and accepted documents for establishing identity in India. It questioned why Aadhaar, considered essential for obtaining various official documents, was excluded while documents like caste certificates were included.
Relevance to Identity, Not Citizenship: The Court emphasized that the Special Intensive Revision (SIR) process is about verifying identity, not citizenship. Since Aadhaar serves that purpose effectively, its exclusion lacked justification.
Non-Exclusivity of Document List: The Court highlighted that the Election Commission’s list of 11 acceptable documents was not exhaustive, and in the interest of justice, Aadhaar, EPIC, and ration cards should also be considered valid for voter registration.
What issues surround the timing and conduct of the SIR in Bihar?
Short and Rigid Timelines: The Supreme Court noted that the 30-day deadlines for citizens to verify and submit documents were too short, raising concerns about procedural fairness.
Unclear Classification of SIR: The Court observed that the Bihar SIR was neither “summary” nor “special” as defined under Section 21 of the Representation of the People Act, 1950, making the exercise appear legally ambiguous.
Why is Aadhaar controversial in proving voter citizenship?
Not a Proof of Citizenship: The Aadhaar Act clearly states that Aadhaar is meant for identity verification, not citizenship confirmation. It can be issued to non-citizens who are residents, which makes it unreliable as evidence for voting eligibility.
Risk of Inclusion Errors: Using Aadhaar may result in non-citizens being wrongly enrolled as voters due to data inaccuracies or misuse, thereby compromising the integrity of the electoral rolls.
High Dependence Among Marginalised Groups: In regions like Bihar, 87% of people have Aadhaar, but few possess documents like passports or matriculation certificates. If Aadhaar is excluded, vulnerable citizens risk disenfranchisement, raising concerns about equity and access.
What are the issues related to the Adhaar Card and NPR in India?
Overlap of Purpose and Confusion on Citizenship: While Aadhaar is officially a tool for identity verification and welfare delivery, and NPR is for creating a register of residents, their perceived linkage with citizenship screening (especially post-CAA debate) has led to widespread fear and confusion. Eg: During the 2020 NPR update, several states (e.g., West Bengal, Kerala) halted implementation, citing concerns over its potential use for citizenship determination.
Privacy and Data Security Concerns: Both Aadhaar and NPR involve massive collection of personal data, but the legal and technological safeguards for privacy and misuse remain inadequate. Aadhaar has faced leaks, while NPR has been criticised for seeking sensitive demographic data without clear purpose. Eg: In 2018, UIDAI acknowledged multiple cases where Aadhaar data was accessible through public domains or appswithout authorisation.
Exclusion due to Documentation Gaps: Aadhaar and NPR can inadvertently exclude individuals lacking proper documentation—especially the poor, migrants, or marginalised groups—from public services or the voter list. Eg: Reports from Jharkhand revealed cases where lack of Aadhaar linkage led to denial of PDS rations, contributing to hunger-related deaths.
Way forward:
Strengthen Legal Safeguards and Clarity: Enact clear legislative guidelines to distinguish the roles of Aadhaar, NPR, and citizenship documentation, ensuring they are not misused for exclusionary practices. A robust data protection law must accompany these measures.
Promote Inclusion and Transparency: Ensure all government identity and registration drives are conducted with public awareness, grievance redressal mechanisms, and opt-out provisions for vulnerable groups, to prevent exclusion and build trust in institutions.
Mains PYQ:
[UPSC 2014] Two parallel run schemes of the Government viz. the Adhaar Card and NPR, one as voluntary and the other as compulsory, have led to debates at national levels and also litigations. On merits, discuss whether or not both schemes need run concurrently. Analyse the potential of the schemes to achieve developmental benefits and equitable growth.
Linkage: This PYQ directly relates to the essence of the statement “Consider Aadhaar, EPIC, ration card as proof” by focusing on the Aadhaar Card and the debates and implications surrounding its use as a governmental tool.
The United Nations Environment Programme (UNEP), in its latest Frontiers 2025 report titled The Weight of Time, has warned that increased river and coastal flooding caused by climate change could unearth dangerous legacy pollutants from water bodies.
About Legacy Pollutants:
Definition: Legacy pollutants refer to toxic substances like heavy metals and persistent organic pollutants (POPs) that continue to remain in the environment even decades after their use has been banned or restricted.
By-products: Produced from incineration, metal smelting, and waste burning.
Persistence: These substances are highly resistant to environmental degradation and accumulate in riverbeds, lakes, estuaries, and other sediment-rich ecosystems.
Health Hazards: Even at low exposure levels, legacy pollutants can cause: Neurotoxicity (nervous system damage), Immunotoxicity (immune disruption), Hepatotoxicity (liver damage), Reproductive toxicity (infertility, birth defects), Carcinogenicity (various cancers), Endocrine disruption etc.
Sources:
Past industrial practices, use of banned agricultural chemicals, and obsolete pesticide stockpiles.
Improperly managed chemical landfills, which still hold an estimated 4.8–7 million tonnes of POP waste globally.
Key Highlights of Frontiers 2025: The Weight of Time (UNEP):
Retreat of Toxins: Climate change-induced flooding can unearth and redistribute toxic legacy pollutants from contaminated sediments into the environment and food chain.
How? Floodwaters re-suspend heavy metals and POPs trapped in sediment.
Case Studies Cited:
Hurricane Harvey (Texas, 2017): Released mercury and carcinogenic chemicals from flood-induced sediment dispersal into Galveston Bay.
The National Education Society for Tribal Students (NESTS) and UNICEF India launched TALASH (Tribal Aptitude, Life Skills and Self-Esteem Hub), a first-of-its-kind national initiative for holistic development of tribal students in Eklavya Model Residential Schools (EMRSs).
About the TALASH Initiative:
Overview: TALASH (Tribal Aptitude, Life Skills and Self-Esteem Hub) is a national programme launched by the National Education Society for Tribal Students (NESTS) in partnership with UNICEF India.
Target Group: It is aimed at the holistic development of tribal students studying in Eklavya Model Residential Schools (EMRSs) across the country.
Objectives: The initiative fosters self-awareness, emotional resilience, life skills, and career clarity among tribal youth.
Focus: It is the first national initiative in India designed specifically for tribal students.
Broader Policy: TALASH aligns with the National Education Policy 2020, promoting inclusive, equitable, and competency-based education.
Coverage Goal: Over 1,38,336 students across 28 States and 8 Union Territories are expected to benefit.
Implementation: By the end of 2025, TALASH aims to be implemented in all EMRSs nationwide.
Key Features of TALASH:
Psychometric Assessments:
Inspired by NCERT’s ‘Tamanna’, TALASH offers aptitude tests to help students discover their interests, abilities, and potential.
Based on the results, students receive Career Cards suggesting suitable career options.
Career Counselling: The platform offers structured career guidance to help students make informed decisions aligned with their strengths and aspirations.
Life Skills & Self-Esteem Modules: TALASH teaches communication, problem-solving, emotional regulation, and self-confidence through interactive modules.
E-Learning for Teachers:
A dedicated online portal provides training and resources to teachers to help them mentor students effectively.
So far, 189 teachers from 75 EMRSs have been trained to lead school-level sessions.
[UPSC 2017] With reference to ‘National Skills Qualification Framework (NSQF)’, which of the statements given below is/are correct?
1. Under NSQF, a learner can acquire the certification for competency only through formal learning.
2. An outcome expected from the implementation of NSQF is the mobility between vocational and general education.
Select the correct answer using the code given below:
Options: (a) 1 only (b) 2 only* (c) Both 1 and 2 (d) Neither 1 nor 2
Researchers from Birbal Sahni Institute of Palaeosciences (BSIP), Lucknow, have found strong evidence that the Kashmir Valley, now cool and temperate, was once a warm, humid subtropical region.
About the Study on Fossils:
Site of Fossil Discovery: The fossils were recovered from the Karewa sediments of the Kashmir Valley, known for preserving ancient plant remains.
Analysis: Researchers used CLAMP (Climate Leaf Analysis Multivariate Program) to analyze fossil leaf shape, size, and margins to estimate past temperature and rainfall patterns.
Coexistence Approach: It was also used, comparing fossil plants with their modern relatives to reconstruct the region’s ancient climate.
Key Findings:
Past Climate Type: The Kashmir Valley once had a warm, humid subtropical climate, very different from the cool, Mediterranean-type climate it experiences today.
Vegetation Evidence: Fossilized leaves showed diverse subtropical plant types no longer found in the region’s current vegetation.
Role of Tectonic Uplift: The tectonic uplift of the Pir Panjal Range was identified as a key factor that blocked the Indian summer monsoon from entering the valley.
Climatic Transition: This led to gradual drying of the region and a shift from subtropical forests to temperate ecosystems.
Impact of Mountain-Building: The study shows that mountain-building (tectonic uplift) can directly affect climate patterns by altering monsoon routes.
Relevance to Climate Change: The findings provide insight into natural climate shifts over millions of years, helping contextualize modern climate change.
Ecological Vulnerability: It also highlights the fragility of mountain ecosystems like the Himalayas, which are vulnerable to both natural and human-induced environmental changes.
Back2Basics:
Karewa Sediments: They are plateau-like terraces in the Kashmir Valley, made up of lacustrine (lake) and fluvio-glacial deposits; They are known to preserve ancient fossils, especially of plants.
Subtropical Climate: A warm and humid climate with moderate to high rainfall, supporting dense vegetation. Ex: Climate of northeastern India.
Mediterranean-Type Climate: Characterized by mild, wet winters and hot, dry summers; Ex: Current climate of parts of the Kashmir Valley.
[UPSC 2025] Which of the following are the evidence of the phenomenon of continental drift?
I. The belt of ancient rocks from Brazil coast matches with those from Western Africa. II. The gold deposits of Ghana are derived from the Brazil plateau when the two continents lay side by side. III. The Gondwana system of sediments from India is known to have its counterparts in six different landmasses of the Southern Hemisphere.
Options: (a) I and III only (b) I and II only (c) I, II and III * (d) II and III only
Union Home Minister recently highlighted that 83% of issues discussed in Zonal Council meetings have been resolved, reaffirming their role as effective platforms for intergovernmental cooperation.
What are Zonal Councils?
Establishment: They are statutory bodies established under the States Reorganisation Act, 1956; they are not constitutional bodies.
Purpose: Their main goal is to promote cooperation and coordination among states, union territories, and the central government.
Basis for Zoning: Zones were drawn based on natural divisions, cultural and linguistic affinity, river systems, and security needs.
Zonal Division: India is divided into five zones—Northern, Central, Eastern, Western, and Southern—with a separate Zonal Council for each:
Central Zonal Council: Chhattisgarh, Uttarakhand, Uttar Pradesh, Madhya Pradesh
Eastern Zonal Council: Bihar, Jharkhand, Odisha, West Bengal
Western Zonal Council: Goa, Gujarat, Maharashtra, Dadra & Nagar Haveli, Daman & Diu
Southern Zonal Council: Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, Puducherry
Note:
North-Eastern Council (NEC)(separate body): Assam, Arunachal Pradesh, Manipur, Tripura, Mizoram, Meghalaya, Nagaland, Sikkim (added in 2002)
The union territories of Andaman and Nicobar Islands and Lakshadweep are NOT members of any of the Zonal Councils. However, they are presently special invitees to the Southern Zonal Council.
Composition and Structure of Zonal Councils:
Chairperson: Each Zonal Council is chaired by the Union Home Minister.
State Representation: The Chief Ministers of all states in the respective zone are members of the Council.
Additional Members: Each state nominates two additional ministers; administrators of union territories also participate.
Vice-Chairperson Role: The role of Vice-Chairperson rotates annually among the Chief Ministers.
Standing Committees: These are formed with Chief Secretaries of states and meet ahead of full sessions to finalize the agenda.
Functions and Responsibilities:
Cooperation & Consensus: Promote interstate and Centre-state cooperation through dialogue and consensus-building.
Key Issues Addressed: Economic and social planning, Border disputes, Inter-state transport, Linguistic minority concerns etc.
Advisory Role: While the councils’ recommendations are advisory, they play a vital role in dispute resolution and coordinated policy formulation.
Recent Developments and Significance:
Leadership in NEC: In 2018, the Union Home Minister became the Chairperson of the North Eastern Council, signaling a push for broader integration.
Revitalization under Modi Government: Zonal Councils have evolved into dynamic, action-oriented platforms rather than passive advisory bodies.
Strengthening Federalism: These councils now actively contribute to cooperative federalism, resolve disputes, and accelerate regional development.
Efficacy in Implementation: With 83% of agenda issues resolved, Zonal Councils demonstrate increasing political will and effectiveness in addressing regional challenges.
[UPSC 2013] Which of the following bodies is/are not mentioned in the Indian Constitution?
1. National Development Council 2. Planning Commission 3. Zonal Councils
Select the correct answer using the codes given below.
Options: (a) 1 and 2 only (b) 2 only (c) 1 and 3 only (d) 1, 2 and 3
This article maps AI’s promises, pitfalls, ethics and India‑specific policy pathways. UPSC tends to wrap this theme in open‑ended, multi‑layered mains prompts—one year it focuses on sectoral impact and privacy (GS 3 2023), the next on ethical dilemmas in governance (GS 4 2024)—so the examiner expects you to juggle tech facts with values and Indian policy. Many aspirants slip because they parrot definitions of Artificial Intelligence but can’t weave age‑specific stakes from “AI and Age Cohorts in India,” ignore power shifts flagged in “AI’s Expanding Role: From Support System to Decision‑Maker,” or forget to anchor answers in domestic rules like “Policy and Ethics for Human‑Centric AI in India.” This article fixes those gaps by giving plug‑and‑play illustrations (AI tutors translating into 22 languages for rural kids; Google Health AI reading X‑rays; Delhi High Court saying AI can’t decide parole), pairing each with matching ethical or regulatory hooks, and ending with a ready blueprint for laws, audits, and citizen opt‑outs. The standout feature is its age‑cohort matrix: it zeros in on children, youth, workers, and the elderly in parallel, letting you lift tailor‑made examples for any angle the paper throws.
PYQ ANCHORING
GS 3: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 the healthcare? [2023]
GS 4: The application of Artificial Intelligence as a dependable source of input for ad ministrative rational decision-making is a debatable issue. Critically examine the statement from the ethical point of view.[2024]
Human agency — the power to make free, informed choices — is the backbone of dignity and democracy. But in the age of Artificial Intelligence, that agency stands at a crossroads. AI now shapes how we learn, work, heal, and even vote. It promises precision, efficiency, and reach — yet it also risks turning people into mere data trails and automated outcomes.
As the Human Development Report 2025 warns, AI must augment human freedom, not silently erode it. The real question isn’t whether AI is good or bad — it’s who it’s working for. Are we building AI to serve human choices — or are we quietly rewiring ourselves to fit the logic of machines?
AI and Age Cohorts in India
Children (0–14 years)
Opportunities
Present Problems
1. AI tutors can adapt to each child’s level, making learning more inclusive (e.g., vernacular platforms translating content into 22+ Indian languages).
1. Over 60% of rural schoolchildren lack consistent internet/device access for AI-based learning (ASER Report, 2023).
2. SMS-based or low-data AI tools can help underprivileged kids catch up in basic math and language (e.g., Google’s Read Along app for rural users).
2. Screen overuse is linked to reduced attention and emotional regulation in children under 10 (HDR 2025; AIIMS mental health survey, 2022).
3. AI can create safe, filtered educational videos for children (e.g., YouTube Kids’ restricted mode).
3. Unregulated AI-generated content has been used to create deepfake videos of minors (HDR 2025).
4. AI tools can detect and flag harmful online content, protecting children from abuse (e.g., Microsoft’s Project Artemis).
4. India lacks a robust system to monitor and respond to AI-facilitated child exploitation online (only 6 cybercrime units focus on child abuse – NCRB, 2022).
5. AI can support early learning even in tribal/rural belts where teacher shortages exist (e.g., AI-powered tablets used in Jharkhand pilot programs).
5. Most AI tools are English-centric and ignore regional dialects, leaving large populations behind (India has 120+ spoken languages).
Youth (15–24 years)
Opportunities
Present Problems
1. AI can personalize skill development (e.g., AI-based coding platforms used in Atal Innovation Labs across India).
1. 30% of college students in Tier-2 cities report lack of access to quality tech tools (AICTE survey, 2023).
2. AI-backed learning platforms can adapt to each student’s pace and language (e.g., Khan Academy in Hindi).
2. 1 in 3 teenagers feel social media worsens anxiety or self-esteem due to AI-generated content feeds (HDR 2025).
3. Entry-level workers benefit from AI-based support systems (e.g., call center trainees improved by 14% in task resolution using AI assist – HDR 2025).
3. Most online AI training is concentrated in metros; rural youth miss out on upskilling (NITI Aayog Digital Skills Report, 2022).
4. Youth can use AI for civic participation, storytelling, or activism (e.g., AI-based media projects in colleges).
4. High misinformation exposure due to AI-curated social media; 45% of youth admit they can’t tell fake news from real (PRS Youth & Tech Study, 2023).
5. AI can help youth find jobs via better matching and interview prep (e.g., LinkedIn AI features for resume review).
5. AI platforms often reinforce bias in job screening (e.g., non-English resumes flagged more often – Harvard-IDinsight India study, 2021).
Working-Age Adults (25–59 years)
Opportunities (with examples)
Present Problems (with data/examples)
1. AI tools can increase productivity in jobs like analytics, customer support, and logistics (e.g., Wipro’s AI-based productivity suite).
1. 44% of Indian workers fear being replaced by AI, especially in mid-skill roles (PwC Future of Work survey, 2023).
2. AI-enabled upskilling platforms (e.g., Coursera, Skill India Digital) can help workers shift to new roles.
2. Less than 10% of India’s workforce has received any formal digital or AI-based training (IndiaSkills Report, 2023).
3. AI can automate paperwork and repetitive tasks, freeing workers to focus on creative or decision-based work (e.g., TCS automating HR workflows).
3. Workers in small firms often face AI-based surveillance without consent or understanding (HDR 2025; reports from garment and delivery sectors).
4. Farmers and small entrepreneurs can use AI tools for weather forecasting, pricing, and crop planning (e.g., Microsoft’s AI Sowing App in Andhra Pradesh).
4. Informal workers (93% of India’s workforce) often lack access to smartphones or awareness about AI tools.
5. AI can support mental health monitoring in workplaces (e.g., AI chatbots like Wysa in Indian corporate wellness programs).
5. Indian workers report increased stress due to AI-based performance monitoring systems (e.g., delivery apps with algorithmic deadlines – Labour Ministry, 2022).
Elderly (60+ years)
Opportunities (with examples)
Present Problems (with data/examples)
1. AI health tools can monitor chronic conditions remotely (e.g., wearable BP monitors linked to AI dashboards).
1. Over 66% of Indian seniors say they find digital tools confusing or untrustworthy (HelpAge India Survey, 2022).
2. Telehealth in local languages via AI can help seniors in remote areas consult doctors (e.g., eSanjeevani AI pilots).
2. Many elderly still lack smartphones or live alone without digital support (Census 2011: 20 million elderly live alone).
3. AI voice assistants (e.g., Alexa in Hindi) can help with reminders, news, and companionship.
3. Seniors often report feeling more isolated when human caregivers are replaced by tech (HDR 2025).
4. AI can help predict early signs of illnesses like Alzheimer’s through speech or behavior tracking.
4. Most health AI tools aren’t tailored for elder-specific needs (font size, voice clarity, regional preferences).
5. Community-based AI training (e.g., digital literacy camps run by NGOs) can improve confidence and inclusion.
5. Lack of government-run AI training programs for seniors means the digital divide widens with age.
AI’s Expanding Role: From Support System to Decision-Maker //MAINS
Artificial Intelligence has quietly outgrown its role as a behind-the-scenes assistant. No longer limited to data crunching or recommendations, AI now actively influences, automates, and in some cases, replaces human decision-making. Whether in classrooms, clinics, or courtrooms, algorithms are shaping choices that were once purely human. This shift marks a profound change — from AI as a tool we control, to AI as a force we must increasingly negotiate with.
Understanding the Shift in AI’s Role
Sector
What AI Does Now
What That Means
Healthcare
AI triages patients, reads X-rays, and suggests diagnoses (e.g., Google Health AI tools)
Doctors may rely on AI inputs before making treatment decisions — it’s not just support, it’s guidance.
Hiring & HR
AI screens CVs, shortlists candidates, and even assesses facial expressions in interviews
Employers may never see a candidate the algorithm filters out. AI shapes who gets a shot.
Education
Adaptive platforms adjust what students see next, based on performance (e.g., Byju’s, Khan Academy)
Teachers increasingly follow AI cues, altering the curriculum journey for each child.
Justice & Policing
In some countries, AI helps predict crime hotspots or recidivism risks (e.g., COMPAS in the U.S.)
Raises ethical flags — AI can influence bail, sentencing, and policing focus.
Finance & Credit
AI assesses loan applications, flags fraud, and scores creditworthiness (e.g., SBI’s AI-backed lending tools)
People’s financial futures can hinge on opaque algorithmic scores — often with no recourse.
The shift isn’t just technological — it’s political and ethical. The more AI shapes core life decisions, the more we need to ask: who programs the program, and who remains accountable when it fails?
AI and Human Development
AI has the power to enhance human agency — giving people more control, access, and ability to make informed choices. But it also holds the potential to erode that same agency through manipulation, opacity, and overreach. The HDR 2025 makes it clear: AI must be designed to empower, not overpower. Below is a dual lens on how AI can both build and break our freedom to choose.
How AI Can Enhance Human Development
Aspect
How It Empowers
Examples
Personalisation with Autonomy
AI customizes services like learning or healthcare without taking over decisions.
AI-based learning platforms like Khan Academy adapt to a student’s pace while allowing manual override.
Assistive Technologies
Empowers people with disabilities to communicate, navigate, or learn independently.
AI speech-to-text tools and smart prosthetics (e.g., Google’s Project Relate for speech impairment).
Access to Information
Breaks language and literacy barriers; simplifies complex content.
Google Translate, ChatGPT in local languages, and news summarisation tools (Koo AI news in Indian languages).
Human-in-the-Loop Systems
Keeps humans involved in key decisions, reducing blind reliance on AI.
AI in radiology suggests possible diagnoses, but doctors make the final call.
Context-Aware Decision Support
Provides data-driven insights while respecting social or cultural context.
Decisions become unexplainable and unfair, leaving users powerless.
Loan rejection or job shortlisting based on biased datasets (e.g., Amazon’s AI recruiting tool scrapped for gender bias).
Data Colonialism
AI reflects elite/global north values, ignoring local realities or ethics.
Most large language models (LLMs) are trained on Western data; few understand Indian dialects or social contexts.
Overdependence on AI
People lose decision-making confidence, deferring too much to tech.
Over-reliance on GPS weakens spatial memory; patients self-diagnosing from AI health bots.
Surveillance & Nudging
AI manipulates behavior via targeted ads, notifications, or content shaping.
Cambridge Analytica scandal where voter behavior was influenced using personal data.
Automation Anxiety
Fear of being replaced reduces motivation and mental well-being.
In sectors like retail or customer support, AI adoption sparks job insecurity and resistance.
India’s Strategy for an AI Future
As AI becomes deeply embedded in how Indians learn, earn, and live, its design and deployment must be guided by ethics, not just efficiency. For India — a diverse, democratic, and data-rich country — the stakes are higher: AI must be accountable, inclusive, and people-first. Policies must ensure that AI enhances human dignity, not replaces it. Here’s how India can align its AI growth with ethical foundations and constitutional values.
Policy and Ethics for Human-Centric AI in India
Focus Area
What India Must Do
Examples from Indian Context
Ethical AI Frameworks
Build binding standards around fairness, explainability, and accountability. Avoid black-box algorithms, especially in public services.
NITI Aayog’s #ResponsibleAI draft lays groundwork, but India still lacks a comprehensive AI ethics law.
Regulation for Empowerment
Ensure laws protect human decision-making in sensitive sectors like health, law, and education. AI should assist, not replace, doctors, judges, or teachers.
Delhi High Court recently ruled that AI can’t determine parole or judicial outcomes — human discretion is essential.
Transparency & Public Participation
Mandate public review of government AI projects. People have the right to know how AI affects them and offer feedback before rollout.
Lack of consultation on facial recognition systems (like in Hyderabad) triggered privacy concerns.
Data Sovereignty
Create safeguards to ensure Indian data is used for Indian interests, respecting user consent and national control.
India’s Digital Personal Data Protection Act (2023) is a first step; more is needed to regulate how global AI firms use Indian datasets.
Inclusive Design
Involve marginalised communities in AI development to avoid bias and exclusion. AI should reflect India’s languages, values, and diversity.
Most AI tools still lack voice/language support for large parts of rural and tribal India (e.g., Santali, Bhojpuri, etc.).
Way Forward
Legislate a Comprehensive Ethical AI Law Enact binding legal standards ensuring transparency, fairness, explainability, and redress in all AI systems — especially in healthcare, education, welfare, and law enforcement.
Make Algorithmic Decisions Contestable Ensure that every citizen has the right to question, appeal, or opt out of AI-based decisions — from loan rejections to exam scoring or government benefits.
Mandate Public Consultation for Public AI Projects Require pre-implementation audits and citizen consultations for AI use in policing, surveillance, welfare delivery, and education.
Establish an Independent AI Ethics Commission Set up a statutory body to monitor AI deployment across sectors, audit for bias, and certify algorithms — similar to the role of SEBI in financial regulation.
Prioritise Vernacular and Inclusive AI Design Incentivize the creation of AI tools in Indian languages, tailored for rural and underrepresented users — with accessible interfaces for the disabled, elderly, and low-literacy populations.
#BACK2BASICS: INDIA’S AI REGULATION FRAMEWORK // pRELIMS
1. Policy Foundation: NITI Aayog’s Responsible AI Approach
NITI Aayog published two key papers (2020–21) on Responsible AI.
Emphasises five key principles: safety and reliability, equality, inclusivity and non-discrimination, privacy and security, transparency and accountability.
Focus areas include promoting ethical AI, identifying sectoral use-cases (like healthcare, education, agriculture), and enhancing public trust.
However, this framework is advisory in nature and not legally binding.
2. Data Governance Law: Digital Personal Data Protection Act, 2023
India’s first comprehensive data protection law.
Governs how personal data is collected, processed, and stored by digital entities, including AI systems.
Introduces concepts like consent, data fiduciaries, and lawful use of data.
Limitations: Does not cover non-personal data or algorithmic bias, explainability, or accountability directly.
3. Ministry-Led Initiatives: MeitY and IndiaAI
The Ministry of Electronics and IT (MeitY) is the nodal agency for AI strategy and deployment.
Launched the IndiaAI program to build AI infrastructure, promote innovation, and drive skilling.
Draft National Data Governance Framework Policy (2022) aims to make anonymised non-personal data available for innovation.
Supports public–private partnerships, startup funding, and computing access for AI development.
4. Sector-Specific AI Oversight
Sector
Oversight Approach
Finance
RBI regulates AI applications in banking, fintech, credit scoring, and algorithmic trading.
Healthcare
National Health Authority (NHA) uses AI for diagnostics and patient management under Ayushman Bharat. Ethical safeguards evolving.
Policing and Justice
Facial recognition, predictive policing, and surveillance tools used at state and central levels, but lack standardised AI-specific regulation.
Education
EdTech platforms use AI for personalised learning, but are currently unregulated in terms of ethical AI use.
5. Judicial Observations
Courts have begun addressing ethical concerns around AI:
Delhi High Court (2023) held that AI tools cannot replace judicial reasoning in decisions like parole or bail.
Supreme Court has raised concerns about AI-enabled surveillance and its impact on privacy.
There is no binding jurisprudence yet, but increasing judicial scrutiny signals growing concern.
6. Current Gaps and Regulatory Needs
No dedicated AI law or regulatory authority.
Lack of mandatory algorithm audits, bias mitigation, explainability requirements, and redress mechanisms.
No legal provision for the right to explanation or human oversight in automated decision-making.
No registry or audit framework for public-sector AI deployment.
7. Proposed and Emerging Directions
Multiple policy bodies and parliamentary committees have called for:
A dedicated AI Regulation Bill to classify AI applications by risk (e.g., low, high, prohibited).
An independent AI Ethics and Accountability Authority.
Mandatory impact assessments before deploying AI in sensitive areas like health, policing, or education.
Clear user rights such as opt-out options and the right to contest automated decisions.
8. Global Alignment and Engagement
India is participating in international efforts such as:
Global Partnership on AI (GPAI)
OECD AI Principles
G20 discussions on AI safety and regulation
India advocates for a development-first, sovereignty-focused model of AI regulation rather than adopting restrictive Western templates.
SMASH MAINS MOCK DROP
Artificial Intelligence is moving from being a support tool to becoming a decision-maker in sectors like governance, healthcare, and law enforcement. Critically examine the opportunities and ethical challenges this shift presents for a democratic society like India.
The International Buddhist Confederation (IBC) recently celebrated Ashadha Purnima, also known as Dhammachakra Pravartana Divas at Mulagandha Kuti Vihara, Sarnath.
About Dhammachakra Pravartana Divas:
First Sermon: It marks the day when Gautama Buddha delivered his first sermon after attaining enlightenment.
Date of Observance: The day is observed annually on the full moon of Ashadha (Ashadha Purnima), usually in July.
Name and Location: The sermon, called Dhammacakkappavattana Sutta, was delivered at Deer Park (Isipatana), Sarnath, near Varanasi.
Core Teachings Introduced: It laid the foundational teachings of Buddhism by introducing the Four Noble Truths and the Noble Eightfold Path.
Formation of Sangha: His five former ascetic companions—Kaundinya, Bhaddiya, Vappa, Mahanama, and Assaji—became the first monks of the Buddhist Sangha.
Symbolic Representation: The Dharma Chakra (Wheel of Dharma) symbolizes this “turning of the wheel of law” and spread of the Buddha’s teachings.
Significance:
Monastic Practice: It marks the beginning of the Varsha Vassa, a three-month monastic retreat during the rainy season.
Religious Importance: It is the second most important Buddhist festival after Buddha Purnima.
Modern Day Significance:
Ambedkarite Movement: In India, it is also significant for commemorating Dr. B.R. Ambedkar’s conversion to Buddhism with his followers at Deekshabhoomi, Nagpur (14 October 1956).
Social Commitment: On this day, millions reaffirm their commitment to Buddhist values and the 22 vows taken to renounce caste-based discrimination.
Global Observance: The day is celebrated internationally under various names—Esala Poya (Sri Lanka), Asanha Bucha (Thailand), and Asadha Purnima (India).
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[UPSC 2024] What is disaster resilience? How is it determined? Describe various elements of a resilience framework. Also mention the global targets of the Sendai Framework for Disaster Risk Reduction (2015-2030).
Linkage: This PYQ, focusing on “disaster resilience” and “Disaster Risk Reduction (DRR),” provides an excellent framework to discuss how catastrophe bonds (cat bonds) function as a financial planning tool for natural disasters. The article “Catastrophe Bonds: Insuring India’s Future Against Disasters” directly addresses the need for such instruments in India’s disaster management strategy.
Mentor’s Comment: Catastrophe bonds (cat bonds) are in the spotlight as India explores innovative disaster risk financing amid rising climate-related calamities. With low disaster insurance penetration, India is considering cat bonds to strengthen post-disaster response, reduce fiscal shocks, and lead a regional South Asian initiative. Global success stories and India’s proactive mitigation funding have revived interest in adopting this financial tool.
Today’s editorial analyses the Catastrophe bonds (cat bonds). This topic is important for GS Paper III (Disaster Management) in the UPSC mains exam.
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Let’s learn!
Why in the News?
As climate change causes more frequent disasters, countries and insurers are using cat bonds to manage risk. These bonds help raise funds from markets for recovery and rebuilding after disasters.
What are catastrophe bonds?
Catastrophe bonds are risk-linked securities that transfer disaster risk from issuers (usually governments or insurers) to investors. They are triggered when a predefined catastrophic event (like an earthquake, cyclone, or flood) occurs.
Eg: The World Bank issued cat bonds for Mexico and Pacific Island countries to cover tropical cyclone and earthquake risks.
How do they function as instruments for disaster risk financing?
Governments (sponsors) pay premiums, and the principal becomes the insured sum; if a disaster hits, investors lose their principal, which goes to recovery. Intermediaries like the World Bank issue the bond, ensuring reliability and reduced counter-party risk.
They ensure quicker payouts, reduce dependency on budget allocations, and transfer risk away from insurers to global markets.
Why is disaster risk insurance penetration low in India?
Lack of Awareness and Financial Literacy: Many individuals, especially in rural and hazard-prone areas, are unaware of the importance or availability of disaster insurance. Eg:Farmers vulnerable to floods or droughts often rely on government relief instead of purchasing crop insurance.
High Premium Costs and Perceived Low Returns: Insurance premiums are often considered unaffordable or unnecessary, especially when disasters seem unlikely in the short term. Eg: Urban households in seismic zones like Delhi-NCR rarely insure homes against earthquakes.
Limited Private Sector Participation and Poor Outreach: The insurance market remains underdeveloped, with few disaster-specific products and limited last-mile delivery mechanisms. Eg:MSMEs in coastal Odisha remain uninsured despite repeated cyclone exposure due to poor insurer penetration.
How can cat bonds address this gap?
Access to Global Capital Markets: Cat bonds transfer disaster risk from governments to global investors, increasing the funding pool for post-disaster recovery. Eg: After Hurricane Maria (2017), Mexico accessed $150 million via a World Bank-backed cat bond, enabling rapid relief.
Ensure Quick Payouts for Emergencies: Cat bonds use trigger-based mechanisms (e.g. earthquake magnitude, wind speed) to enable fast disbursement of funds. Eg: In 2021, the Philippines received $52.5 million within weeks after Typhoon Rai, due to pre-agreed cat bond triggers.
Reduce Fiscal Pressure on Governments: Pre-disaster financing through cat bonds helps avoid budget shocks and reduce dependency on ad-hoc aid or borrowing. Eg: A cyclone-risk cat bond for Bay of Bengal can pre-finance relief for Odisha and Andhra Pradesh.
How can India benefit from a regional South Asian cat bond?
Shared Risk Pooling for Cost Efficiency: By joining a regional cat bond with countries like Nepal, Bangladesh, and Sri Lanka, India can pool disaster risks, reducing the premium burden and increasing affordability. Eg: The Pacific Catastrophe Risk Insurance Company (PCRIC) pools risk for Pacific island nations, lowering overall costs.
Boosts Regional Cooperation and Preparedness: A shared bond encourages joint early warning systems, emergency planning, and data sharing, improving collective disaster readiness. Eg: SAARC Disaster Management Centre can coordinate common triggers and payout parameters across South Asia.
Access to Larger and Diverse Capital Markets: A regional bond can attract more global investors by offering diversified risk, improving fund availability post-disaster for quick response and recovery. Eg: The World Bank’s Southeast Asia Disaster Risk Insurance Facility (SEADRIF) supports countries like Laos and Myanmar through pooled financing.
What are the key risks in designing and implementing cat bonds?
Basis Risk (Mismatch Between Trigger and Actual Loss): There’s a risk that the bond may not pay out even when severe losses occur, if the predefined trigger (e.g., earthquake magnitude or rainfall level) is not met, undermining trust and utility.
High Setup and Transaction Costs: Cat bonds require specialized modeling, legal structuring, and investor engagement, which may be too complex or expensive for lower-income or disaster-prone regions without external support.
Why should India diversify its disaster financing amid climate risks?
Rising Frequency and Intensity of Disasters: Climate change is increasing the number of extreme weather events like floods, cyclones, and droughts. Sole reliance on budgetary support and relief funds is unsustainable, making diversified financing (like cat bonds, parametric insurance) essential.
Reducing Fiscal Burden and Ensuring Faster Relief: A diversified disaster financing system helps minimize delays in post-disaster response and lessens pressure on state and central budgets, allowing for quick payouts and resilient recovery.
Way forward:
Promote Risk-Based Financing Instruments: Encourage the use of catastrophe bonds, parametric insurance, and public-private partnerships to diversify disaster risk funding and ensure timely payouts.
Strengthen Institutional Capacity and Data Systems: Develop robust disaster risk assessment tools, improve climate modelling, and integrate early warning systems to design effective and credible financial instruments.
