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Type: Explained

These Newscards correspond to the explained section of various newspapers. They become immensely important for both prelims and mains and special attention needs to be paid to them

  • Govt. to spend Rs 24,000 crore to modernise police force

    Govt. to spend Rs 24,000 crore to modernise police force

    Why in the News

    The Union government has told the Supreme Court that it has begun implementing an umbrella Police Modernisation Mission worth Rs 24,000 crore over the next five years.

    What is the Police Modernisation Mission?

    1. Its form: It is an umbrella scheme, meaning several police modernisation components are funded through a single mission rather than as separate schemes.
    2. Its size and horizon: The outlay is Rs 24,000 crore, to be spent over five years.
    3. Who it covers: It targets the internal security capabilities of both State police forces and the Central Armed Police Forces.
    4. Its stated route: The capability gain is to come through greater use of technology, which is the only delivery mechanism named in the submission.

    Why was the disclosure made in a court proceeding?

    1. The proceeding was begun by the Court itself: The suo motu case was initiated in 2025 after the Court took note of a media report on non functional CCTV cameras at Udaipur police stations.
    2. The Court widened it into a compliance review: It sought compliance reports from the Centre, the States and the Union Territories on the installation and functioning of cameras.
    3. The Bench: The matter is before a Bench of Justices Vikram Nath and Sandeep Mehta, with the Centre represented by an Additional Solicitor-General.
    4. The mission answers the compliance question with an outlay: The Centre’s response to a record of equipment not working is a larger programme to buy equipment, and no separate maintenance or functioning guarantee was placed before the Court.

    What did Paramvir Singh Saini versus Baljit Singh require?

    1. Cameras at specified locations: The 2021 judgment mandated CCTV cameras at key locations in police stations, including lock ups and the rooms of inspectors and sub-inspectors.
    2. Cameras of a specified capability: The directions required night vision and audio recording, so that an interrogation is recorded and not merely observed.
    3. Footage retention: Recordings were to be preserved for a stated minimum period, so that a complaint filed months later can still be tested against the record.
    4. Oversight bodies: State level and district level oversight committees were to be constituted to purchase, maintain and monitor the systems and to review footage.
    5. Notice to the public: Police stations were to display notices telling visitors that the premises are under camera cover and that a complaint of human rights violation may be made.

    Challenges to the Police Modernisation Mission

    1. Modernisation money has historically gone unspent: Releases under police modernisation schemes stall on State matching shares and pending utilisation certificates. Eg. Successive Comptroller and Auditor General audits have flagged underutilisation of police modernisation grants by States.
      The Fix: Release tranches against verified physical milestones, meaning equipment installed and functioning, rather than against expenditure statements.
    2. Central money buys equipment, not reform: Police is a State subject under Entry 2 of the State List, so a central mission can fund hardware without touching recruitment, tenure or accountability. Eg. Directions in Prakash Singh versus Union of India (2006) on fixed tenure and a State Security Commission remain only partly implemented across States.
      The Fix: Condition a share of each State’s mission grant on enactment of the police board and fixed tenure directions.
    3. Technology fails at the point of maintenance: Installed systems stop working for want of annual maintenance contracts, spares and power backup, and the capital grant does not cover them. Eg. Audits have found Crime and Criminal Tracking Network and Systems terminals installed but not in use at a large number of police stations.
      The Fix: Fund a five year maintenance and consumables line inside each equipment sanction, instead of leaving it as a separate State liability.
    4. Manpower shortfall caps what technology can deliver: A camera or a database still needs an officer to operate, review and act on it, and State forces run well below sanctioned strength. Eg. Bureau of Police Research and Development data records an actual police strength close to 150 personnel per lakh population, against the United Nations recommended figure of 222.
      The Fix: Tie mission approval to a State recruitment schedule closing sanctioned vacancies across the same five years.
    5. Surveillance capacity grows faster than the oversight around it: Equipment installed for accountability also expands the force’s own recording and identification capability, with no independent auditor of its use. Eg. Access logs for police station footage are held and reviewed by the same force whose conduct the footage records.
      The Fix: Place footage access logs and retention compliance under an independent State level oversight body publishing an annual report.

    Conclusion

    The mission has moved from announcement to implementation, and it was disclosed in a proceeding about equipment already mandated and not functioning. Buying capability and sustaining it are different problems, and only the first has an outlay attached to it. The next point to watch is the compliance reports the Court has sought from the Centre, the States and the Union Territories, which is where the gap between equipment sanctioned and equipment working becomes visible.

    Back2Basics: Central Armed Police Forces

    1. What they are: Seven armed forces of the Union under the Ministry of Home Affairs, distinct both from the armed forces under the Ministry of Defence and from State police.
    2. The seven forces: Central Reserve Police Force, Border Security Force, Central Industrial Security Force, Indo-Tibetan Border Police, Sashastra Seema Bal, Assam Rifles and the National Security Guard.
    3. How they are used: They are deployed to States on requisition for internal security duty, election duty and disaster response, and guard specified international border sectors.
    4. Command and recruitment: Each is headed by a Director General, with officer recruitment through the Union Public Service Commission and other ranks through the Staff Selection Commission.

    [2023, GS3, 15 marks] What are the internal security challenges being faced by India? Give out the role of Central Intelligence and Investigative Agencies tasked to counter such threats.

  • India and Belgium ramp up bilateral defence cooperation

    India and Belgium ramp up bilateral defence cooperation

    Why in the News

    India and Belgium have signed three government level defence agreements, ramping up a defence relationship that had carried no framework instrument.

    What was signed at the government level?

    1. A Letter of Intent on Defence Cooperation: Signed by the two defence ministries, it covers training, officer exchanges, research and development, seminars, joint exercises and maritime security.
    2. An industry to industry Memorandum of Understanding (MoU): It links the Belgian Security and Defence Industry association with the Society of Indian Defence Manufacturers.
    3. A law enforcement MoU: The Central Bureau of Investigation (CBI) and the Belgium Federal Police agreed to cooperate on transnational organised crime, cybercrime and related matters.

    Which capability areas does the defence cooperation target?

    1. Maritime and undersea systems: Mine countermeasures, autonomous maritime systems, underwater robotics and sensors are named focus areas.
    2. Critical infrastructure protection: The list extends to protection of ports, pipelines and subsea data cables.
    3. Conventional and emerging systems: Ammunition, radar, electro optical sensors, command and control, and counter drone systems are covered.
    4. The engagement machinery: The two Defence Ministers agreed to expand contact through a defence cooperation dialogue, high level visits, training and capacity building, and acknowledged the need for greater maritime security collaboration in the Indo-Pacific.

    What was announced alongside the signed instruments?

    1. A resident defence presence in Brussels: India announced the appointment of a Defence Attache at its Embassy in Brussels.
    2. A trade and investment channel: A fast trade mechanism was established to handle trade and investment, alongside a commitment to double bilateral trade over the next five years.
    3. A Consular Dialogue: A standing consular channel was established between New Delhi and Brussels.
    4. Private sector agreements: At least ten private defence agreements were sealed during the visit, including production of Belgian military items such as rockets in India.

    Where does the economic relationship currently stand?

    1. Merchandise trade: Bilateral trade stood at $13.01 billion in 2025-26.
    2. Investment: Belgian foreign direct investment into India was about $4.2 billion between April 2000 and December 2025.
    3. The Belgian trade position: The Belgian side described the global situation as turbulent and called for free trade and an end to the unilateral imposition of tariffs.

    What did the two sides agree on regional and global security?

    1. The Pakistan assurance: India raised concerns over Belgian defence technology or expertise reaching Pakistan, and received an assurance that there is no question of such cooperation.
    2. Terrorism: The Belgian side supported India’s campaign against cross border terrorism and condemned the Pahalgam terror attack.
    3. Maritime routes: The joint statement called for the safety and security of maritime routes and for safe and unimpeded maritime shipping, in the context of the conflicts in West Asia and Ukraine.
    4. Conflict resolution: Both sides supported efforts aimed at an early end to the conflicts in Ukraine and West Asia, and backed a just peace in Ukraine consistent with the United Nations Charter.
    5. A shared historical marker: The two leaders paid tribute to the more than 9,000 Indian soldiers who died at Flanders Fields during the First World War.

    Challenges to India Belgium defence cooperation

    1. A Letter of Intent creates no obligation: It records agreed areas of work and binds neither side to a contract, a value or a timeline. Eg. India’s defence industrial roadmaps with European partners have taken years to convert into signed production contracts.
      The Fix: Attach a dated work plan with a named nodal agency on each side, reviewed at every defence cooperation dialogue.
    2. Export clearance does not sit with the federal government alone: Belgian arms export licences are issued at regional government level and operate under the European Union common position on arms exports. Eg. Flanders and Wallonia license equipment produced in their own regions separately.
      The Fix: Negotiate a programme level licence assurance at the time of contract, instead of clearance obtained shipment by shipment.
    3. Joint production usually stops at final assembly: Technology transfer in Indian defence tie ups has historically covered assembly rather than the propellant, seeker or sensor core. Eg. Several ammunition and rocket partnerships have delivered kits assembled in India from imported subsystems.
      The Fix: Write a phased indigenous content schedule into each private agreement, measured at component level rather than by value.
    4. A political assurance is not a contractual clause: An undertaking on third country transfers given in a bilateral meeting is not enforceable in any signed instrument. Eg. The assurance on Pakistan was conveyed through officials rather than recorded as a treaty obligation.
      The Fix: Convert the undertaking into an end use and non transfer clause in every follow on agreement signed under the Letter of Intent.
    5. The trade base is narrow: The exchange is dominated by a single commodity group, so a doubling target rests on a thin sectoral spread. Eg. Antwerp’s diamond trade accounts for the bulk of India Belgium merchandise flows.
      The Fix: Set named non gem sectoral milestones under the fast trade mechanism, so the target is measured outside the diamond trade.

    Conclusion

    A relationship built largely on trade has acquired a defence framework in the space of a single visit. What has been signed is intent, an industry linkage and a police cooperation channel, and the substance now depends on what follows them. Two things are worth watching: whether the private production agreements reach contract, and whether the trade target is pursued in sectors outside the commodity group that currently dominates the exchange.

    Back2Basics: Society of Indian Defence Manufacturers

    1. What it is: The apex industry body representing Indian defence manufacturers, which acts as the single interface between the domestic defence industry and the Ministry of Defence.
    2. Origin: It was set up in 2017, promoted by the Confederation of Indian Industry.
    3. Membership: It spans defence public sector undertakings, large private manufacturers and micro, small and medium enterprises in the defence supply chain.
    4. What it does: It signs cooperation agreements with counterpart industry associations abroad, and represents industry positions on procurement policy and indigenisation.

    [2023, GS2, 15 marks] ‘The expansion and strengthening of NATO and a stronger US-Europe strategic partnership works well in India.’ What is your opinion about this statement? Give reasons and examples to support your answer.

  • US settlement with Meta is a start. India must protect itself

    US settlement with Meta is a start. India must protect itself

    Why in the News

    Meta has agreed to pay up to $17.1 billion to resolve child harm claims brought by a bipartisan coalition of attorneys general across the United States, its territories and the District of Columbia.

    What does the settlement require Meta to do?

    1. The scale and the date: The agreement was reached on 26 August and ranks among the largest consumer protection settlements in internet history.
    2. Default time limits and night restrictions: Users under 18 get default limits on time spent and restrictions on night time use.
    3. Limits on notifications during school hours: The company must curb notifications sent to minors while school is in session.
    4. Age assurance: The settlement requires enhanced measures to establish whether a user is a minor before the account is treated as an adult account.
    5. Independent compliance oversight: Compliance with the safeguards is monitored by an independent party rather than reported by the company itself.

    Why does the penalty carry little punitive weight?

    1. The sum is small against the revenue base: The company generated $201 billion in revenue in 2025, and the settlement is payable over 10 years.
    2. The market read it as a cost, not a shock: The stock rose 5 per cent after the settlement was announced.
    3. The reforms are the substance, not the money: The mandated safety changes go to how Facebook and Instagram are allowed to operate for minors, and they are overdue rather than novel.

    Why has India’s own debate produced no comparable outcome?

    1. The cycle is episodic and self closing: A tragedy occurs, outrage follows, a platform issues a statement, a parliamentary question may be asked, and silence returns.
    2. The harm is not less serious here: The absence of Indian legal action reflects the absence of a process capable of compelling answers, not a smaller problem.
    3. Regulatory attention has been lighter than in the West: Global platforms have operated in India with weaker oversight and lower public awareness than they face in other large markets.

    What did the American case produce that India lacks?

    1. Court compelled discovery: The litigation forced the company to produce internal research, design documents and executive communications about child safety, under oath, in public and subject to cross examination.
    2. The questions India cannot currently ask: What internal research shows about the mental health impact on Indian teenage girls, how the recommendation engine behaves in Hindi, Tamil and Bengali for a fourteen year old at 11 pm, and how many Indian children under 13 are active on platforms that legally prohibit their membership.
    3. The unmeasured scale of abuse material: The scale of child sexual abuse material affecting Indian users and the manner of its reporting are not on any public record. Eg. In the United States alone, 7.5 million such materials were under internal review.
    4. Whether the same design was applied here: If the addictive design features at issue in the American cases were applied to Indian users, those users have been exposed to the same harm with none of the protection.

    What legal tools does India already hold?

    1. The statutory base already exists: The Consumer Protection Act, 2019, the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, the Protection of Children from Sexual Offences (POCSO) Act, 2012, the Juvenile Justice (Care and Protection of Children) Act, 2015 and the Constitution together cover the conduct alleged.
    2. A regulator level inquiry: The National Commission for Protection of Child Rights (NCPCR), the statutory body for child rights, can open a formal inquiry compelling platforms to produce India specific safety research, algorithm documentation, data on underage users and internal harm research.
    3. Direct recourse for families: Affected families can approach consumer forums and High Courts directly, without waiting for a regulator to act first.
    4. Coordinated State litigation: State governments can file consumer protection and child safety suits in Indian courts, and a single State moving first can trigger a wider set of filings.
    5. The policy standard is already stated: The Safe, Trusted and Accountable framework developed in 2021 was built so that platforms operating at scale bear legal responsibility for the consequences of their design choices.

    Why is new legislation still needed?

    1. Existing law compels disclosure only case by case: Each of the routes above produces documents inside one proceeding, so nothing survives the case that produced it.
    2. A statutory right to algorithmic disclosure: Parliament can create an obligation on platforms to reveal their content moderation policies, recommendation engine parameters and child safety research for Indian users.
    3. A standing recipient rather than a court: The disclosure would run to a designated Indian authority, which turns a litigated exception into a continuing duty.

    Challenges to compelling platform disclosure in India

    1. No child rights regulator holds standing discovery power: A statutory commission can summon information, and it cannot compel sworn production of internal research open to cross examination. Eg. Platform responses to Indian regulators are routinely filed as written submissions rather than as evidence tested in a hearing.
      The Fix: Give the child rights commission discovery powers with a stated penalty for non production, on the model available to a commission of inquiry.
    2. Consumer forums cannot read algorithmic evidence: A district or State consumer commission has no technical assessor able to interpret recommendation engine documentation. Eg. Consumer adjudication in India is built around defective goods and deficient services, not around product design telemetry.
      The Fix: Attach a standing panel of technical assessors to the National Consumer Disputes Redressal Commission for platform cases.
    3. The evidence sits outside Indian process: Internal research and design documents are held on servers abroad and reached through mutual legal assistance. Eg. Mutual legal assistance requests to the United States for platform records routinely take more than a year to return.
      The Fix: Write a production obligation for India specific safety research into intermediary due diligence, so the duty attaches to operating in India rather than to where a server sits.
    4. Safe harbour blunts liability for design: Section 79 of the Information Technology Act, 2000 shields intermediaries for third party content, and design and ranking choices are argued into that shelter. Eg. Platforms have defended recommendation ranking as an automated function rather than as an editorial act.
      The Fix: Separate design and ranking decisions from hosting in the due diligence rules, so safe harbour covers content and not product architecture.

    Conclusion

    Platform accountability in India has been argued at the level of statements and outrage, never at the level of evidence. The material that would establish whether Indian children were exposed to the same design choices sits with the platforms, and no Indian process currently compels its production. Legislation would convert that into a standing duty, and litigation would produce it once. The marker to watch is whether any Indian regulator or State government files an action carrying discovery powers, rather than another request for information.

    Online child safety in India

    1. What the domain covers: It governs how platforms design products for users below 18, across age of access, consent, exposure to content and collection of data.
    2. The regulatory age is higher than the platform age: Indian data protection law treats anyone below 18 as a child, while platforms set their own account creation floor at 13.
    3. States have moved before the Centre: Karnataka announced plans to bar social media for those under 16, and Andhra Pradesh announced restrictions for those under 13.
    4. The evidence base cited officially: Research highlighted in the Economic Survey 2025-26 records that adolescents lack the neurological brakes needed to resist addictive features such as infinite scroll.

    Laws and Rules Governing Online Child Safety

    1. Digital Personal Data Protection Act, 2023: It treats any individual below 18 as a child, requires verifiable parental consent before processing a child’s data, and prohibits behavioural tracking and targeted advertising directed at children.
    2. The Data Protection Board of India adjudicates breaches and imposes penalties under the Act, with appeals lying to the Telecom Disputes Settlement and Appellate Tribunal.
    3. Information Technology Act, 2000: Section 67B criminalises publishing or transmitting material depicting children in sexually explicit acts, and extends to browsing and downloading such material.
    4. Indian Penal Code and Bharatiya Nyaya Sanhita provisions on obscenity: They cover sale and circulation of obscene material to a person under 20, and operate alongside the specialised child protection statutes.

    Key Facts about Online Child Safety

    1. Australia set a minimum age of 16 for social media accounts through the Online Safety Amendment (Social Media Minimum Age) Act 2024, enforced from December 2025.
    2. Indonesia became the first Southeast Asian country to enforce a ban for under 16s, in March 2026.
    3. Gaming disorder is classified as a health condition in the World Health Organization’s International Classification of Diseases, Eleventh Revision (ICD-11).
    4. Kerala runs Digital De-Addiction centres, known as D-DAD centres, for children showing signs of compulsive device use.

    Challenges in Online Child Safety

    1. Age verification is easily circumvented: A minimum age holds only where the platform can establish age, and self declared dates of birth cannot be checked. Eg. Children open accounts on platforms barring under 13s using a false year of birth or an adult family member’s account.
      The Fix: Move to privacy preserving age estimation processed on the device, rather than to identity document uploads.
    2. Verification itself creates a new privacy risk: Establishing age through selfies, identity documents or bank details assembles a fresh database of minors’ sensitive data. Eg. Document based age checks require a child to hand a platform the exact identifiers the law is trying to keep from it.
      The Fix: Require age signals to be discarded once the check is complete, with a bar on retaining the underlying document.
    3. A ban pushes use underground: Restriction moves minors to less regulated services and to tools that hide their location. Eg. Teenagers migrate to smaller platforms or route access through virtual private networks.
      The Fix: Replace a binary ban with a graduated model, strict restriction under 13, supervised access from 13 to 15, and full access at 16.
    4. Restriction removes support networks for some children: Online communities are the only peer support available to some minors, and a blanket bar cuts that too. Eg. LGBTQ+, neurodivergent and disabled children frequently depend on such communities.
      The Fix: Exempt verified support, counselling and helpline services from minor account restrictions.

    [2025, GS2, 15 marks] The National Commission for Protection of Child Rights has to address the challenges faced by children in the digital era. Examine the existing policies and suggest measures the Commission can initiate to tackle the issue.”

  • Police camera ‘caught’ murder, rape accused at Jantar Mantar protest

    Police camera ‘caught’ murder, rape accused at Jantar Mantar protest

    Why in the News

    The Delhi Police has told the Supreme Court that its Facial Recognition System (FRS) spotted 2,873 people with criminal antecedents at the main protest site at Jantar Mantar between 20 and 26 July. The submission follows a Supreme Court order quashing every First Information Report (FIR) arising from the exam leak student protests.

    What is the Delhi Police’s Facial Recognition System?

    1. What the software does: It places boxes around faces detected in a camera feed and compares them against images held in police databases.
    2. The threshold for a positive match: A match is treated as positive at an accuracy rate of 80 per cent, a figure the force disclosed in a 2022 reply under the Right to Information (RTI) Act, 2005.
    3. What it searches against: Of the 2,873 flags, 2,402 were attributed to Crime Kundli, the force’s own biometric database, and 471 to criminal records.
    4. What the output is not: A match is not by itself proof of identity, and performance varies with the algorithm, camera angle, lighting, image quality, masks and the database being searched.

    What does the offence-wise breakdown in the affidavit show?

    1. The residual category is the largest by far: 1,884 of the 2,873, close to two thirds, sit under other Indian Penal Code, Bharatiya Nyaya Sanhita and special law entries rather than under any named serious offence.
    2. The legal status of those flagged is unstated: The affidavit does not specify whether the people identified were accused, convicts, or merely named in criminal cases.
    3. The database is claimed to hold only serious offenders: The affidavit states that the face and other material of only those accused facing serious offences are in the police record, and not those facing petty offences such as traffic violations.
    4. The geographic concentration: The North district recorded the highest count at 285, followed by Outer at 257, North West at 256, North East at 174, East at 173 and South West at 166. Railways, Crime Branch, IGI Airport, Metro and the Special Cell were among the other units listed.

    What did the record check of 205 flagged individuals find?

    1. The sample examined: The 205 comprised 101 murder accused, 61 rape accused, 6 accused under the Protection of Children from Sexual Offences (POCSO) Act, 2012, and 37 of the 62 listed under attempt to murder.
    2. The finding: At least 25 of them were lodged in the Tihar, Mandoli or Rohini prison complexes at the time the system flagged them, according to police, jail and court records.
    3. The composition of the 25: 17 were accused in murder cases, 4 in rape cases of which 3 were under the POCSO Act, and 4 in attempt to murder cases.
    4. The dates of the flags: Three of the 25 were identified on 24 July, 21 on 25 July and one on 26 July, the final day of the protest.

    Why does the police assurance not settle the question?

    1. Verification is the only safeguard on record: The stated position is that action follows only after field verification establishes that the person was in fact present at the site, and no verification standard, timeline or reporting duty accompanies that assurance.
    2. Verification is still pending at scale: The force has stated that further verification of the identified individuals is pending, which leaves 2,873 names on a list that a court has already permitted the government to act on.
    3. The accuracy threshold is an internal setting, not a legal standard: An 80 per cent match is a configuration choice inside the software, and no statute, rule or judicial direction fixes what confidence level may be relied on before a person is named.
    4. The error is not random noise: People held in custody were placed at a protest site by the system, which points to database and matching failure rather than to a borderline image.

    Challenges to facial recognition in policing

    1. No statutory basis governs deployment: India has no law authorising or limiting police use of facial recognition, so procurement, matching thresholds and retention are set administratively. Eg. The Delhi Police’s 80 per cent threshold became public only through a Right to Information reply, not through a published rule.
      The Fix: Require prior legislative authorisation and a published operating standard for any biometric identification system before it is deployed in a public space.
    2. Accuracy falls sharply for some groups: Error rates in facial recognition are higher for darker skin tones, women and younger faces, so the burden of a false match is not evenly spread. Eg. The United States National Institute of Standards and Technology’s evaluation of commercial algorithms recorded higher false positive rates across demographic groups.
      The Fix: Mandate a published demographic error audit of the deployed algorithm before each operational use, with results filed with the sanctioning authority.
    3. The system was built for one purpose and used for another: A database assembled to trace missing persons or match crime scene images becomes a crowd screening tool without any fresh authorisation. Eg. The Delhi Police’s facial recognition capability was originally acquired for tracing missing children.
      The Fix: Attach a statutory purpose limitation to each biometric database, so any new use requires a separate written sanction that is placed on record.
    4. Surveillance at a protest changes who turns up: Recording and matching faces at an assembly deters lawful participation independently of any action that follows. Eg. Cameras mounted on police vans at the Jantar Mantar site were visible to those attending.
      The Fix: Bar identification of participants at a lawful assembly except on a written order naming a specific cognisable offence under investigation.
    5. There is no route to contest a match: A person flagged by the system is not told, so the error surfaces only if a journalist or a court checks the records. Eg. The 25 custodial mismatches came to light through a newspaper’s record check, not through any internal review.
      The Fix: Require written notice to every individual against whom a biometric match is acted on, with a stated procedure to seek correction of the underlying record.

    Conclusion

    A facial match is being treated as a sufficient basis to proceed against a named list, while the force’s own position is that a match establishes nothing on its own. Both cannot hold at once. Nothing on record fixes what field verification must consist of, who performs it, or who checks that it happened. The point to watch is whether the Court requires the verification outcome for each flagged individual to be filed before any action follows.

    [2024] Under which of the following Articles of the Constitution of India, has the Supreme Court of India placed the Right to Privacy?

    (a) Article 15

    (b) Article 16

    (c) Article 19

    (d) Article 21

  • ‘OBC lists were not used for Census as they featured classes, not castes’

    Why in the News

    The Union government has settled the 2027 Census on an open column method of recording caste, under which every caste outside the Presidential Scheduled Caste and Scheduled Tribe lists is written down as the household states it. The Central and State lists of Other Backward Classes (OBCs) were considered as the alternative and rejected, on the recorded ground that the list of OBCs is a list of classes and not a list of castes. The Union Cabinet had approved the inclusion of caste in the Census forms a year after the Opposition campaigned for a caste census, and the need to enumerate the OBC population was that campaign’s main argument. The method now chosen produces no OBC count of its own, which is the point the Leader of the Opposition in the Lok Sabha and the Congress president are contesting. This is the first Census to enumerate caste beyond the Scheduled lists since 1931.

    What is the open column method of caste enumeration?

    1. The household’s own answer is recorded: The enumerator writes the caste name as it is stated, without matching it against a list drawn up in advance.
    2. The Scheduled categories stay list based: Scheduled Caste and Scheduled Tribe communities continue to be enumerated against the corresponding Presidential lists, as has always been done.
    3. Classification is a separate, later step: The raw names collected are grouped into categories after enumeration is complete, rather than at the doorstep.

    Why were the Central and State OBC lists rejected?

    1. Several entries name something other than a caste: The lists carry entries describing occupational groups, settler groups, and a specific class of labourers.
    2. The examples cited are concrete: Officials pointed to “local borns” in the Andaman and Nicobar Islands and tea garden workers in Assam.
    3. Such entries are a minority of the lists: They sit among nearly 3,000 communities classified as OBC across the Central and State lists.
    4. The same community changes category across States: Several communities carried on OBC lists are classified as Scheduled Caste or Scheduled Tribe depending on the State.
    5. The State survey route was assessed on the same test: The problem surfaced when the government examined whether the methodology of State conducted caste surveys, such as those in Bihar and Telangana, could be replicated nationally.

    What is the objection to the open column?

    1. It yields no enumerated list of communities: OBC groups and Opposition leaders want the communities named, listed and counted specifically rather than written in freehand.
    2. The 2011 precedent is the stated worry: The Socio Economic and Caste Census of 2011 threw up over 46 lakh caste names, which critics expect an open column to reproduce.
    3. The government has used that same result before: It cited the 46 lakh names as its reason for not releasing the caste data from that exercise.
    4. The utility of the method is what is questioned: The objection is not that the count will not happen, but that its output will not be usable for policy.

    Does the government’s own record support the reason it gave?

    1. A statutory body concluded the opposite: A 2015 National Commission for Backward Classes document held that a caste can be, and quite often is, a social class in India.
    2. That document treated caste as the workable starting unit: It recorded that caste represents an existing, identifiable social group, and that an exercise can begin there and then extend to other groups, sections and classes.
    3. The choice was made at the top of the system: Officials involved in the methodology recorded that each option carried its own advantages and drawbacks, and that the open column was finalised only after the alternatives were considered at the highest levels.

    Challenges to caste enumeration through an open column

    1. Spelling and synonym variants inflate the count: One community is recorded under several names across districts, dialects and languages, and each variant enters the data as a separate entity. Eg. Bihar’s 2023 caste survey recorded 215 distinct castes because its enumerators worked from a fixed list rather than a blank field.
      The Fix: Publish a standardised State wise caste directory before enumeration and map every write-in entry to it during data processing.
    2. The classification authority is not named in advance: Grouping raw names into Backward Class and other categories is a decision taken after the count by a body the enumeration design does not identify. Eg. An expert group was constituted in 2015 to classify the caste data collected in the 2011 exercise, and that data was never released.
      The Fix: Notify the classifying authority, its composition and its publication timetable before the first form is filled.
    3. Self reported caste responds to incentive: A household may report the name that improves its standing or its eligibility rather than the one it ordinarily uses. Eg. Karnataka’s 2015 socio economic and educational survey drew objections from dominant communities over its recorded counts and stayed unpublished for years.
      The Fix: Verify a sample of write-in entries against household level administrative records before the totals are finalised.
    4. The quality of the answer rests on the enumerator: A caste question asked without a fixed probe sequence produces a sub-caste from one household and a broader cluster name from its neighbour. Eg. Census enumeration is carried out by roughly 30 lakh school teachers and government staff deployed for a few weeks.
      The Fix: Script the caste question with a mandatory probe sequence and test every enumerator on it before deployment.

    Conclusion

    The method of collection is now settled. What is not settled is who converts several lakh written answers into a list of communities, and by what rule. That step, and not the column on the form, is what decides whether the exercise produces a usable Backward Class number at all. It sits outside the methodology the government has announced, and it has no published owner.

    Back2Basics

    1. The Census is conducted under the Census Act, 1948 and the rules framed under it, which make participation compulsory and the individual returns confidential.
    2. It is carried out by the Office of the Registrar General and Census Commissioner of India, which functions under the Ministry of Home Affairs.
    3. It is decennial, and the last completed round was in 2011, the 2021 round having been deferred.
    4. The 2027 round runs in two phases, houselisting followed by population enumeration, with a reference date of 1 March 2027 and 1 October 2026 for snow bound areas.

    “[2023, GS1, 15 marks] Why is caste identity in India both fluid and static?

  • Perils of comparing GDP from different base years

    Why in the News

    The Ministry of Statistics and Programme Implementation (MoSPI) has released output data for the first quarter of 2026-27, showing gross domestic product (GDP) growth of 7.8 per cent in real terms and 10.3 per cent in nominal terms. A former Finance Secretary alleged that the corresponding quarter of the previous year had been revised down to produce a flattering comparison, and computed nominal growth of only 2.6 per cent. That computation takes its numerator from the new 2022-23 base year series and its denominator from the discontinued 2011-12 series.

    What does a base year revision do?

    1. The base year anchors the price comparison: A base year is the reference year whose prices are used to strip inflation out of output, so that real growth measures volume rather than price change.
    2. Revision is routine and was overdue: Every economy revises its base year, normally once in about five years. The absence of a revision was itself a reason India’s GDP was losing credibility.
    3. It is an opportunity to rebuild the estimate: A revision lets the government bring in new data sources, improve methodology and capture an economy that has changed since the last base.
    4. It changes real GDP measurement first: Nominal GDP is measured at current prices, so a change of base year does not by itself explain a fall in the nominal series.

    What did the first quarter data show?

    1. Growth beat the expectation set at the start of the quarter: Most economists expected about 7.5 per cent for April to June. The official figure came in at 7.8 per cent in real terms.
    2. The quarter opened in the middle of a war: The West Asia conflict was disrupting output across the world, and India’s heavy dependence on West Asian energy imports was expected to slow growth further.
    3. The world did not contract either: The International Monetary Fund (IMF) expects world growth of 3.0 per cent in 2026 against 2.9 per cent in the previous year, so an economy withstanding the shock is not by itself anomalous.

    Why is the 2.6 per cent claim invalid?

    1. The rollback happened before the war, not after the result: The new series was unveiled on 27 February 2026, one day before the United States went to war with Iran. Nominal GDP for the first quarter of 2025-26 was rolled down that day from Rs 86.1 trillion on the old series to Rs 80.3 trillion on the new one.
    2. Later revisions were marginal: The same quarter was estimated at Rs 80.4 trillion in June and Rs 80.0 trillion on 31 August, against Rs 88.3 trillion for the first quarter of 2026-27.
    3. The sequence rules out reverse engineering: The base was rolled down six months before the current quarter’s number existed, so the previous year’s figure was not cut to flatter it.
    4. The same method produces an absurd result on real GDP: Applied to the real series, mixing the old denominator with the new numerator implies growth of almost 70 per cent in the quarter.

    What question does the revision genuinely leave open?

    1. The first half of 2025-26 lost about Rs 11 lakh crore: Nominal GDP for the first two quarters fell from Rs 171.30 lakh crore on the old series to roughly Rs 160 lakh crore on the new one, a cut of about 6.5 per cent concentrated in those two quarters.
    2. There is nothing left to reconcile against: The old series was discontinued before comparable third and fourth quarter estimates for 2025-26 were published, so no complete old series year exists to match quarter by quarter.
    3. The demand is for a reconciliation bridge: The revision should be broken down in rupees into revised source data, changed sectoral coverage, methodological changes, revised taxes and subsidies, and changed price indices and deflators, for GVA as well as for GDP.
    4. The long run picture is comparable: Nominal GDP rose about 32.8 per cent under the old series and 32.3 per cent under the new one over 2022-23 to 2025-26, and cumulative real growth is broadly similar.
    5. A downward revision is not lost output: The economy did not shrink by Rs 11 lakh crore. Better data can move a historical estimate down.
    6. The annual number moved too: Nominal GDP for 2025-26 was revised from Rs 357 trillion on the old series to Rs 345 trillion on the new one.

    Challenges to India’s national income estimation

    1. Informality is estimated rather than counted: A large share of output comes from unregistered units that no annual return captures, so their contribution is inferred from proxies. Eg. The unincorporated sector is covered by a sample survey, and its output after the 2020 lockdown was derived from indicators rather than enumerated.
      The Fix: Link the enterprise surveys to Goods and Services Tax and Udyam registration data to build a live frame for small units.
    2. Deflators historically overstated value addition: Single deflation applies one price index to output without separately deflating inputs, so a squeeze on firms’ margins is recorded as extra production. Eg. Manufacturing GVA in the 2011-12 series was criticised for a decade on exactly this ground.
      The Fix: The 2022-23 series abolished single deflation, and producer price indices published from June 2026 must now be extended to services.
    3. No back series accompanies the new base: Users cannot compare the new estimates with earlier decades without a consistent recomputed history. Eg. The back series produced for the 2011-12 base was itself contested and withdrawn from circulation.
      The Fix: Publish a full recomputed back series alongside the new base rather than after a lag.
    4. Credibility is contested politically rather than statistically: Each release is judged as a verdict on the government instead of as an estimate with a stated method, which crowds out technical scrutiny. Eg. The IMF has previously raised issues with India’s national income estimates.
      The Fix: Restore a fixed publication calendar for the National Statistical Commission’s own review reports, so scrutiny is institutional rather than episodic.

    Conclusion

    The methodological point is settled and the credibility point is not. A series can be more accurate than the one it replaced and still be harder to interrogate, because the comparison the public used to make has been withdrawn. Confidence in official statistics is built by letting an independent reader reproduce the numbers, not by asserting that the method was correct. The larger unresolved problem sits behind the estimate: output is growing fast and is not generating enough good quality jobs, which is how a demographic dividend turns into a demographic burden.

    [2021, GS3, 10 marks] Explain the difference between computing methodology of India’s Gross Domestic Product(GDP) before the year 2015 and after the year 2015.”

  • The gap in manufacturing sector GVA

    Why in the News

    An alternative estimate of India’s manufacturing output puts gross value added (GVA, the value a sector adds after the cost of the inputs it consumed is deducted) at Rs 27.4 lakh crore for 2023-24. The National Statistical Office (NSO), in the new National Accounts Statistics (NAS) series, puts the same figure at Rs 38.6 lakh crore. The official number is higher by 40.9 per cent.

    How is manufacturing GVA estimated?

    1. The sector is measured in two parts: The organised part covers registered factories employing 10 or more workers with power, or 20 or more without power, including registered companies. The other part covers unincorporated workshops and household units outside the corporate and factory sector.
    2. One survey covers each part: The ASI reports the production accounts of the factory sector. ASUSE covers the unincorporated sector.
    3. The two surveys together are near complete: Their combined output represents almost the whole of manufacturing GVA, so their sum is a usable independent estimate.
    4. Corporate filings partially replace the factory survey: The official series uses company balance sheet data from MCA-21 for organised manufacturing. The practice began with the 2011-12 base revision and continues in the latest revision with minor modifications.

    Why is the gap traced to organised manufacturing?

    1. The official estimate exceeds the survey based one by 40.9 per cent: Rs 38.6 lakh crore against Rs 27.4 lakh crore for 2023-24 at current prices. The official figure is 14.7 per cent of GDP.
    2. The informal segment cannot explain the divergence: ASUSE is the source for the unincorporated sector in both estimates. That segment contributes 13.9 per cent of manufacturing GVA.
    3. Only the corporate route is left: The divergence must therefore arise in the estimation of organised manufacturing output, where the balance sheet data replaces the survey.

    Does the employment check close the gap?

    1. A large body of workers is unaccounted for: The Periodic Labour Force Survey (PLFS, the official household survey that measures employment and unemployment) estimated 697.5 lakh manufacturing workers in 2023-24. The ASI and ASUSE datasets together captured 532.9 lakh.
    2. The residual is 164.6 lakh workers: These workers produce output that neither survey records, and they are the first candidate for explaining the gap.
    3. Companies outside the survey frame are added too: 2,72,534 MCA companies sit outside the 78,618 private companies captured in ASI data. Most of them are likely to be non factory private companies.
    4. Their potential output is small: Applying technical ratios, meaning output per worker ratios derived from unit level ASI and ASUSE data, the residual workers and companies add Rs 3.6 lakh crore. The alternative estimate rises to Rs 31.0 lakh crore.
    5. A fifth of the official figure stays unexplained: Rs 31.0 lakh crore is 24.5 per cent below the official estimate, at 80.3 per cent of it. Rs 7.6 lakh crore, or 19.7 per cent of official manufacturing GVA, remains unaccounted for.

    Why is the official explanation contested?

    1. The stated official defence: The ASI is establishment based, so it does not capture value addition that occurs inside an enterprise but outside factory premises, in head office, marketing and distribution, or research and development functions.
    2. The evidence cited against it: A 2018 study in the Economic and Political Weekly found that the available evidence does not support that view, so the missing head office value addition cannot carry a gap of this size.
    3. The alternative suspicion is the scaling method: The official procedure scales up sample estimates of active companies to the full universe of registered companies. The size and composition of that universe are unverified.

    Challenges to the official manufacturing GVA estimate

    1. The company universe is unverified: Scaling a sample of active filers onto the full corporate register counts companies that have stopped operating. Eg. The Ministry of Corporate Affairs struck off more than 2 lakh companies from the register in 2017 for failing to file returns.
      The Fix: Publish an annual active company frame reconciled against Goods and Services Tax filings before it is used for scaling.
    2. The unit of measurement changes between sources: The ASI counts factories and MCA-21 counts companies, so one firm with several plants enters the two datasets on different terms. Eg. The 2011-12 base revision inserted the company based route into a series that until then rested on the factory based survey alone.
      The Fix: Publish a factory to company concordance so the two frames can be matched establishment by establishment.
    3. The methodology is not open to outside checking: Neither the MCA data nor the scaling procedure is available for independent replication, so a disputed figure cannot be settled by evidence. Eg. The National Statistical Commission’s 2018 back series report was withdrawn from the public domain shortly after its release.
      The Fix: Release anonymised unit level MCA-21 data and the full estimation procedure to researchers on a fixed schedule.
    4. Informal manufacturing is measured least well: ASUSE misses the smallest own account units, so the segment most exposed to shocks is estimated rather than enumerated. Eg. Output of unincorporated units after the 2016 demonetisation and the 2020 lockdown was inferred from indicators rather than counted.
      The Fix: Run ASUSE at a higher frequency and link it to the Udyam registration database for a live enterprise frame.

    Conclusion

    Whether the official figure is a fuller description of ground reality or an overestimate of output cannot be settled from outside the statistical system. The dispute has moved from arithmetic to access. Opening the corporate filings and the estimation procedure to independent verification is the only step that would close it. Every downstream number built on manufacturing GVA, from sectoral growth to the investment rate, carries the same doubt until that happens.

    [2023, GS3, 10 marks] Faster economic growth requires increased share of the manufacturing sector in GDP, particularly of MSMEs. Comment on the present policies of the Government in this regard.

  • Can AI claim copyright for original work? A question of authorship

    Can AI claim copyright for original work? A question of authorship

    Why in the News

    India’s Copyright Office has rejected an application seeking copyright registration for an artwork generated by an artificial intelligence (AI) system. The application was filed by American computer scientist Stephen Thaler for a work titled ‘A Recent Entrance to Paradise’, which he said had been generated autonomously by his AI system DABUS. The application named DABUS as the author and Thaler as the owner of the copyright. The order is among the first Indian decisions to address who, if anyone, is the author when an AI system generates a work. The tension it exposes is that the Office found the image original enough to qualify for protection while holding that the entity that produced it cannot be an author.

    What is DABUS?

    1. The system: DABUS stands for Device for the Autonomous Bootstrapping of Unified Sentience, an AI system developed by Thaler.
    2. The claim made for it: The application asserted that DABUS had generated the artwork autonomously, rather than as an output directed by a human operator.

    What did the application claim and what did the Office ask?

    1. The filing: Thaler applied in 2022 to register copyright in the artwork.
    2. The first question put to him: The Copyright Office asked whether an AI system could legally be recognised as an author under the Copyright Act, 1957.
    3. The second question: It also asked who should be treated as the author if the work was indeed generated using AI.
    4. The offer he refused: During the proceedings the Office allowed Thaler to amend the application and identify himself as the author. He declined, and continued to insist that DABUS be recognised instead.

    How does the Copyright Act, 1957 treat originality?

    1. The three separate questions: The Act answers whether a work is original, who its author is, and who owns the copyright, and these are distinct questions rather than one.
    2. The protection provision: Section 13 protects original literary, dramatic, musical and artistic works.
    3. The Act does not define originality: The Copyright Office therefore interprets it from Eastern Book Company v. D.B. Modak.
    4. The judicial test: The Supreme Court in that case held that a work need not be novel or groundbreaking to receive copyright protection. It must show at least a minimum degree of creativity, and it cannot be merely copied or mechanically reproduced.

    How does the Act treat authorship and ownership?

    1. The authorship provision: Section 2(d)(vi) identifies the author of a computer generated work as “the person who causes the work to be created”.
    2. The disputed phrase: The dispute was over whether that phrase refers to the machine producing the output or to the person creating and operating the system.
    3. First ownership: Section 17 states that the author is generally the first owner of the copyright.
    4. Transfer: Sections 18 and 19 allow copyright to be assigned or transferred through legally recognised agreements.
    5. What the structure assumes: The Office noted that these provisions are built around legal persons who can hold rights, transfer them and enforce them.

    What did the Copyright Office decide?

    1. Originality was satisfied: The Office found that the image generated by the AI was original enough to qualify for copyright protection.
    2. Authorship is a legal status: The Act treats authorship as a legal status carrying rights and responsibilities, and an AI system, however sophisticated, does not presently possess such recognition under Indian law.
    3. The tool test: To interpret who “causes” a computer generated work to be created, the Office looked to American copyright cases distinguishing between a tool and the person handling it.
    4. DABUS as the tool: Although DABUS generated the final image, it did so within a system designed and set in motion by Thaler, so DABUS was treated as the tool and Thaler as the person who legally caused the work to be created.
    5. Person means natural or juristic: Where an Act refers to a “person” it usually means a natural person or a juristic person such as a company, an entity capable of owning property and entering contracts. DABUS is not a recognised juristic person.
    6. The outcome: Thaler was held to be the person capable of being identified as the statutory author, so the application as filed did not meet the criteria under the Act.

    Why was the fallback request also rejected?

    1. What was sought: Thaler asked in the alternative that DABUS be recorded as the technological generator of the work.
    2. The register cannot confer status: The Office held that the register could not be used to indirectly confer legal status on an AI system.
    3. A procedural ground as well: No proper application seeking such an entry had been made.

    What has the order left open?

    1. A future application can succeed: The order leaves open the possibility of a fresh application that identifies the author in the manner the Copyright Act, 1957 requires.
    2. The change of law is reserved: Any broader change in the law would have to come from Parliament.
    3. The stated limit on administrative power: The order records that whether legal personhood or authorship should ever be extended to autonomous artificial intelligence “remains a policy decision strictly reserved for Parliament, and cannot be introduced via administrative reinterpretation”.

    Challenges to fitting AI generated works into copyright law

    1. Human contribution is not measurable at the point of registration: A registrar cannot tell from the output whether a prompt involved creative choice or a single instruction. Eg. The United States Copyright Office refused registration for the AI generated images in the comic ‘Zarya of the Dawn’ while protecting the human written text and arrangement.
      The Fix: Require a disclosure of AI involvement and of the specific human contribution as a mandatory field in the registration application.
    2. Training data use is unresolved: Models are trained on protected works without licence, so the lawfulness of the input sits behind every question about the output. Eg. Indian news publishers and a music industry body have sought to intervene in the Delhi High Court proceedings against OpenAI on this ground.
      The Fix: Legislate a statutory text and data mining exception with a transparency obligation on training corpora, so the boundary is set rather than litigated case by case.
    3. Ownership defaults to the operator rather than the investor: Treating the person who causes creation as the author leaves the platform, the model developer and the user with competing claims over the same output. Eg. Generative service terms typically assign output rights to the user by contract, which no statute confirms.
      The Fix: Make the allocation of rights in computer generated output a default statutory rule that contracts may vary, rather than leaving it to terms of service alone.
    4. Term of protection has no anchor without a human author: Copyright duration runs from the author’s lifetime, which cannot be computed where the generating entity does not die. Eg. The United Kingdom sets a fixed 50 year term for computer generated works precisely to avoid this problem.
      The Fix: Provide a fixed term measured from the date of creation for works with no identifiable human author.
    5. Enforcement needs an accountable person: Liability for infringing output, and standing to sue over it, both require someone the law can reach. Eg. An autonomously generated image that reproduces a protected character leaves no party with a stated duty under the current provision.
      The Fix: Attach statutory responsibility for infringing output to the person who deployed the system, mirroring the authorship rule the Office has applied.

    Conclusion

    The order settles who the author is and leaves untouched what the author did. A work the law accepts as original was produced by a process its named author did not perform, and the statute has no category for that gap. Parliament is the only body that can create one. The point to watch is whether computer generated works are taken up as a legislative question, or whether the issue keeps returning through individual registration applications and appeals against their refusal.

    Back2Basics

    1. Enactment: The Copyright Act, 1957 came into force in January 1958 and is India’s governing copyright statute.
    2. Administration: It is administered through the Copyright Office, which functions under the Department for Promotion of Industry and Internal Trade.
    3. Coverage: It protects literary, dramatic, musical and artistic works, along with cinematograph films and sound recordings.
    4. Registration is optional: Copyright arises on creation of the work, and registration serves as evidence rather than as the source of the right.

    [2014, GS3, 12 marks] In a globalised world, intellectual property rights assume significance and are a source of litigation. Broadly distinguish between the terms – copyrights, patents and trade secrets.”

  • River-linking is not the solution

    River-linking is not the solution

    Why in the News

    The Union Home Minister used the Southern Zonal Council meeting at Mamallapuram to press for early resolution of water sharing disputes in the southern region, and to propose linking major rivers from the Brahmaputra to the Godavari and the Cauvery.

    Why does the Pennaiyar case undercut the promise of early resolution?

    1. The grievance: Tamil Nadu is aggrieved over what it terms a violation of the 1892 inter State agreement by Karnataka.
    2. The request and the parallel litigation: Tamil Nadu asked the Centre in November 2019 to establish a tribunal. It also moved the Supreme Court with the same demand.
    3. Negotiation without settlement: Two negotiation committees have been formed since then and 11 meetings have been held.
    4. A court direction, then an extension: The Supreme Court in February directed the Centre to form the tribunal within a month, and later extended the deadline by six months. The adjudicatory body is still not in place.
    5. The referral suggestion: The Centre asked the court whether the Pennaiyar dispute could be referred to the Mahadayi Water Disputes Tribunal instead of constituting a new one, although there is nothing in common between the two disputes.
    6. The statute does not allow it: The Interstate River Water Disputes Act, 1956 does not permit such a referral.
    7. A second unanswered demand: The Central government has not replied to Tamil Nadu’s demand, made in March this year, for a tribunal on the Mekedatu dam project proposed by Karnataka.

    What are the objections to inter-linking?

    1. The proponents’ claim: Supporters of river linking, Tamil Nadu among them, hold that the intent is not to disturb the natural flow of any river but to divert a portion of surplus water.
    2. The claim on surplus is disputed: Many experts are not convinced, and expect that once linking is allowed, benefiting regions will demand water even in times of distress.
    3. The original beneficiary loses: That escalation would eventually deprive the original beneficiaries of their quota, which converts a transfer of surplus into a redistribution of entitlement.
    4. The ecological objection: Kerala has stoutly opposed the Pamba-Achankovil-Vaippar link proposal, on the ground that it will affect the Vembanad wetland system, into which the Pamba and Achankovil rivers drain.
    5. The agency’s answer: The National Water Development Agency, the central body that prepares feasibility studies for inter-basin transfer links, says it has accounted for improving the flow of rivers in lean periods.

    What is the record of inter-basin transfer in India?

    1. A thin record over 130 years: In the last 130 odd years the country has seen only a handful of inter-basin transfer projects, most of them in south India.
    2. The projects treated as successes: The Mullaperiyar dam, the Parambikulam-Aliyar project, the Krishna Water Supply Project and the Indira Gandhi Canal Project are regarded as successful examples of inter-basin transfer.
    3. An institution without output: A Special Committee for Interlinking of Rivers was formed after 2014 and has held over two dozen meetings, without much headway.
    4. The one project that moved: The foundation stone for the ₹44,000 crore Ken-Betwa Link Project was laid in 2024.
    5. Its social cost surfaced immediately: That project has led to agitations by tribal populations in Chhatarpur.

    Why is supply side expansion reaching its limit?

    1. Land is the binding constraint: Land is becoming scarcely available for projects of this size.
    2. Acquisition faces organised resistance: Resistance among people is growing when it comes to land acquisition.
    3. The consequence for project design: The days of implementing mega irrigation projects are almost over, which removes the delivery route the linking proposal depends on.

    What does demand side management require?

    1. A shift in the object of policy: Governments at the Centre and in the States, and civil society, need to focus on demand side management instead of perpetually seeking supply side interventions.
    2. Conservation as the priority: The priority has to be conserving what is available and using it judiciously.
    3. A programme aimed at the farmer: A massive programme of sensitising and incentivising farmers on the optimal use of water has to be launched.
    4. The subsidy that drives extraction: Indiscriminate extraction of groundwater, facilitated by free electricity for agriculture in many States, is paving the way for ecological disaster and has to be curbed immediately.

    Challenges to inter-basin water transfer proposals

    1. Surplus is asserted rather than measured: A basin is declared surplus on hydrological series that predate current withdrawal and cropping intensity, so the transferable volume is an estimate that has never been revalidated. Eg. Peninsular link proposals rest on assessments framed decades before present groundwater draft in the same basins.
      The Fix: Publish a revalidated basin water budget, with the assessment year stated, before any link component is taken up for investment approval.
    2. Himalayan links depend on flows that originate outside India: A transfer scheme drawing on the Brahmaputra is exposed to upstream storage decisions India has no treaty right to see. Eg. The Brahmaputra enters India as the Yarlung Tsangpo after a long course through Tibet.
      The Fix: Make a binding upstream flow data arrangement a stated precondition before any Himalayan component of a national grid is sanctioned.
    3. Transferred water carries a permanent energy bill: Peninsular links must lift water across watersheds, so the delivered cost includes pumping power for the life of the project. Eg. Moving water across the Eastern Ghats requires sustained lift rather than gravity flow.
      The Fix: Price transferred water at its delivered cost including pumping energy, so the recipient command area faces the real cost of the supply.
    4. Alignments run through forest and protected areas: Canal alignment and submergence take the least contested land, which in practice is forest and reserve land rather than settled farmland. Eg. The Ken-Betwa link submerges part of the Panna Tiger Reserve.
      The Fix: Require a no alternative alignment finding, tested against a published route comparison, before submergence inside a protected area is cleared.
    5. New supply changes cropping and returns the shortage: A command area that receives assured water shifts to water intensive crops, so demand rises to meet the new supply within a decade. Eg. Long canal commands in western India moved to paddy and sugarcane and developed waterlogging and salinity.
      The Fix: Tie the release of transferred water to a notified crop plan and volumetric delivery through water user associations rather than to area based supply.

    Conclusion

    India is being offered more supply while the reason for the shortage stays untouched. A grid that moves water between basins does not change how the water is used once it arrives. The immediate decision point is the Pennaiyar tribunal, still unconstituted after a court set deadline and an extension of it. Free farm power, and the groundwater extraction it underwrites, is the variable that will decide whether any new transfer capacity is absorbed or simply exhausted.

    Water Resources Management in India

    1. About: Water resources management covers the planning, development and management of water quantity and quality across every use, along with the institutions, infrastructure, incentives and information systems that guide it.
    2. The hydrological imbalance: India has an effective rainfall period of 28 to 29 days in a year, so most annual flow arrives in a short window and has to be stored or lost.
    3. Agriculture dominates demand: Agriculture accounts for around 89 per cent of groundwater extraction.
    4. The institutional home: The Ministry of Jal Shakti was formed in 2019 by integrating two earlier water related ministries.

    Constitutional Framework Governing Water Resources Management

    1. Entry 17, State List: Places water supply, irrigation, canals, drainage, embankments and storage with the States, subject to Entry 56.
    2. Entry 56, Union List: Allows Parliament to regulate inter State rivers and river valleys where it declares such regulation to be in the public interest.
    3. Article 262: Empowers Parliament to provide for adjudication of inter State river water disputes, and to bar the jurisdiction of the courts including the Supreme Court over them.

    Laws and Rules Governing Water Resources Management

    1. Interstate River Water Disputes Act, 1956: Provides for the constitution of a tribunal when a State’s request for adjudication cannot be settled by negotiation.
    2. The 2002 amendment: Fixed a one year limit for constituting a tribunal and a three year limit for the award.
    3. River Boards Act, 1956: Enables the Centre to set up river boards to advise on the regulation and development of an inter State river. No board has been constituted under it.
    4. Dam Safety Act, 2021: Establishes national and State level authorities for the surveillance, inspection and maintenance of specified dams.

    Government Initiatives for Water Resources Management

    1. Atal Bhujal Yojana: Launched in 2019 to improve groundwater management in selected States through community participation.
    2. Pradhan Mantri Krishi Sinchayee Yojana: Expands assured irrigation coverage and promotes micro irrigation under the Per Drop More Crop component.
    3. National Water Mission: Targets integrated water resource management and a 20 per cent improvement in water use efficiency, with the Bureau of Water Use Efficiency set up under it in 2022.

    Challenges in Water Resources Management

    1. Groundwater is extracted faster than it recharges: Assessment blocks in the north west and the south are classified as over exploited, which means annual draft exceeds annual recharge. Eg. Central Ground Water Board assessments place large parts of Punjab, Haryana and Rajasthan in that category.
      The Fix: Extend community level water budgeting with metered abstraction, so a village sees its own draft against its own recharge each season.
    2. Cropping patterns ignore local water availability: Crop choice follows assured procurement and price, not the water the region actually has. Eg. Sugarcane in Marathwada consumes a disproportionate share of a chronically drought affected region’s irrigation water.
      The Fix: Link procurement or price support for water intensive crops to verified micro irrigation adoption on the same holding.
    3. Irrigation charges recover a fraction of the cost: Water charged below the cost of delivering it removes any incentive to use less of it. Eg. Canal water rates in most States do not cover the operation and maintenance cost of the system supplying it.
      The Fix: Move to volumetric supply at the outlet, billed through water user associations rather than assessed on irrigated area.
    4. Basin data is incomplete and not shared: Allocation disputes are argued over rival estimates because no agreed real time record of flows exists. Eg. Rival State claims in southern river disputes rest on differing assessments of the same basin’s yield.
      The Fix: Make real time gauge and groundwater data on one national platform the sole admissible basis for allocation claims.

    Matching Previous Year Question

    “[2017, GS3, 10 marks] Not many years ago, river linking was a concept but it is becoming reality in the country. Discuss the advantages of river linking and its possible impact on the environment.”

  • Fragile ecology, competing interests: The red flags in building Himalayan dams

    Fragile ecology, competing interests: The red flags in building Himalayan dams

    Why in the News

    A glacier collapse near the China Tibet border has triggered floods in Nepal that have killed over 1,100 people, with thousands still missing. The event has renewed expert concern about recent human made changes in a mountain system whose climatic conditions are shifting quickly. 13 hydropower plants, including several under construction projects, were affected.

    Why is the Himalayan system already fragile?

    1. A naturally unstable mountain system: The Himalayas are prone to earthquakes, landslides, avalanches and flash floods before any human intervention is added.
    2. The topography concentrates risk: The region carries lakes formed by melting glaciers, fast flowing rivers and steep slopes, in a zone highly vulnerable to strong earthquakes.
    3. Climate change acts on the pace of natural processes: Temperature change affects the pace and frequency of snow melting and thawing, and of glacial lake outburst floods (GLOFs), which occur when water collected from melting glaciers overflows its containing barrier.
    4. Attribution and risk are separate questions: Linking any single disaster directly to climate change still requires more scientific assessment, and the overall level of risk appears to be increasing.

    How does infrastructure build up compound the toll?

    1. Dams carry a genuine benefit: Dams and reservoirs regulate the flow of water and extend access to services for people living in remote regions.
    2. Construction alters the geology: Building a dam disturbs the geology of the area and makes it more prone to earthquakes, and the drilling and tunnelling required for further projects extends that effect.
    3. Damage runs through the assets themselves: The loss of hydropower plants in this flood dented both generation capacity and access to power.
    4. Exposure has risen with use: Infrastructure build up and high tourist footfall together compounded the disaster’s toll.

    How extensive is Himalayan hydropower now?

    1. Across the Tibetan region: One recent study identified at least 193 dams built or planned across the wider Tibetan region since 2000.
    2. In Nepal: A Nepal hydropower database lists more than 570 projects at different stages.
    3. The largest single project: China is building a massive dam on the Yarlung Tsangpo, the upper course of the Brahmaputra, near Arunachal Pradesh.
    4. A fault beneath it: In July, Chinese researchers flagged an active fault line, a fracture between two blocks of rock, directly beneath the Yarlung Tsangpo mega dam.

    Why is Himalayan dam building also a geopolitical contest?

    1. Infrastructure as a sovereignty marker: Chinese infrastructure building in Tibet is treated by China as a marker of sovereignty over Tibet, not only as an energy programme.
    2. The response is more dams: India, Nepal and Bhutan have responded with their own set of dams, and India is helping Bhutan build a series of hydropower projects.
    3. Signalling and counter signalling: The result is a pattern of signalling and counter signalling in which project decisions answer each other rather than answering the basin’s hydrology.

    What is missing in transboundary cooperation?

    1. No substantial ecosystem cooperation: There has been no substantial cooperation between China and Nepal, or between China and India, on managing the shared ecosystem.
    2. The existing mechanism is narrow: Disasters in the 2000s prompted a memorandum of understanding between India and China in 2002, with an expert level mechanism on transboundary rivers created in 2005. That mechanism has to be expanded to cover other aspects such as GLOFs.
    3. Transparency differs across the border: Nepal officially publishes fairly detailed project and licensing information. Chinese project level information exists but stays scattered across separate official documents and announcements rather than in a comparable consolidated public database.
    4. No real time upstream data: There is no clearly established public system between China and Nepal for continuous, real time sharing of upstream river flow, reservoir operations or glacial lake conditions from Tibet.
    5. Early warning fails at the border: Gaps in information and data sharing between countries complicate early warning for hazards that originate across a boundary.
    6. No arbitration route: Downstream countries lack the consensus to build alliances that can deal with China, and there is no scope for international arbitration. Even a signed agreement would face a state that does not follow such international norms, as the South China Sea dispute shows.

    What would stronger cooperation require?

    1. Continuous data sharing: Cooperation would necessarily include continuous sharing of hydrological, weather and climate data across the boundary.
    2. Paying for upstream observation: Where sustained monitoring carries a cost, downstream countries could co invest in upstream observation systems or pay for specialised datasets, creating a model that benefits both sides.
    3. Standing operational machinery: Automated public warning systems, joint scientific studies and regular emergency exercises would complement the data arrangements.
    4. A landscape rather than a national frame: A nation state centric, container approach does not fit the Himalayas, since these disasters do not confine themselves within national boundaries and their ramifications run across the landscape.

    Challenges to hydropower expansion in the Himalayas

    1. Projects sit in the highest seismic risk zones: Much of the Himalayan arc falls in seismic zones IV and V, so a design earthquake is a live engineering assumption rather than a remote one. Eg. The 2011 Sikkim earthquake damaged structures at the Teesta III project and halted work.
      The Fix: Make site specific seismic hazard assessment and independent design review a published precondition for financial closure, not a post clearance formality.
    2. Sediment load shortens the working life of a project: Himalayan rivers carry among the world’s highest silt loads, which abrades turbines and fills reservoirs faster than design assumptions allow. Eg. Run of the river plants on the Alaknanda and Bhagirathi shut down repeatedly during the monsoon for desilting.
      The Fix: Require measured basin sediment yield data in the detailed project report and size desilting capacity against it rather than against a regional average.
    3. Cascade layouts convert one failure into several: Projects built in series on the same river mean an upstream breach delivers debris and water straight into the next structure. Eg. The 2021 Chamoli flood destroyed the Rishiganga project and then struck the Tapovan Vishnugad project downstream.
      The Fix: Assess clearances at the level of the whole river cascade, so cumulative and cascading failure is evaluated once rather than project by project.
    4. Tunnelling destabilises slopes and drains aquifers: Long headrace tunnels cut through fractured rock, dewater springs and remove support from the slopes above. Eg. Land subsidence in Joshimath in 2023 followed years of tunnelling and construction in the same valley.
      The Fix: Publish pre construction and post construction spring discharge and slope movement monitoring for every tunnelled project, with construction halted on a defined trigger.
    5. Rehabilitation is settled before the risk is understood: Displaced communities are resettled onto land whose hazard exposure has not itself been mapped. Eg. Resettlement colonies for Himalayan projects have been sited on debris fans and old landslide zones.
      The Fix: Require the resettlement site to carry its own hazard clearance before the displacement award is finalised.

    Conclusion

    Himalayan risk now runs through infrastructure as much as through geology. The two positions that cannot both hold are that dams are national assets worth building at scale and that the floods which destroy them cross three borders within minutes, with no obligation on the upstream state to say what is coming. Data sharing, not engineering standards, is the binding constraint on early warning. The concrete thing to watch is whether the India China expert level mechanism is widened past monsoon river flow data to cover glacial lake and reservoir conditions.

    [2023, GS3, 10 marks] Dam failures are always catastrophic, especially on the downstream side, resulting in a colossal loss of life and property. Analyze the various causes of dam failures. Give two examples of large dam failures.”