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GS Paper: GS3-17.Awareness in the fields of IT, Space, Computers, Robotics, Nano-technology, Bio-technology and issues relating to Intellectual Property Rights.

  • Domestic chip design to receive a boost with Rs 1.27 lakh cr push

    Domestic chip design to receive a boost with Rs 1.27 lakh cr push

    Why in the News

    The Centre has notified the operational framework for its Rs 1.27 lakh crore Semicon 2.0 programme, placing the design of Indian chips and the intellectual property behind them at the front of the country’s semiconductor strategy.

    Components of the Semicon 2.0 programme

    1. Support runs across six pillars: At least three of them are devoted entirely to chip design.
    2. Three design incentives are on offer: Chips designed for strategic purposes, chips for the commercial market, and domestically developed chips deployed at scale each attract separate support.
    3. The upstream chain has its own track: Makers of semiconductor materials, chemicals and manufacturing equipment are eligible outside the design pillars.
    4. Fabrication and packaging remain funded: Fabrication plants and advanced chip packaging continue to draw subsidy alongside the design tracks.

    How will the strategic chip design track work?

    1. The government picks the technologies first: It will identify technologies and building blocks, including intellectual property for compute, memory, radio frequency, power, networking and sensors, that it wants developed in India.
    2. The trigger is national importance: The track covers chips meant for areas of national importance and for critical infrastructure.
    3. Selection runs through competitive bidding: The Centre for Development of Advanced Computing (C-DAC), the government’s high performance computing research organisation under the Ministry of Electronics and Information Technology, will issue requests for proposals and select developers.
    4. The state keeps a share of the intellectual property: The intellectual property created under these projects will be jointly owned by the developing company and C-DAC.
    5. Consortiums are permitted: Indian owned and controlled companies can participate independently or alongside global companies, research organisations and academic institutions.

    What does the commercial design track offer?

    1. The target is a fabless industry: The track aims to build commercially viable Indian fabless chip companies, meaning firms that design chips and contract out their manufacture.
    2. Firms get access to design infrastructure: Eligible firms receive electronic design automation (EDA) tools, multi-project wafer fabrication, intellectual property cores, compute sub-systems and post-silicon validation.
    3. Small firms receive seed money: Start-ups and micro, small and medium enterprises (MSMEs) designing commercial chips can receive up to Rs 15 crore or 50 per cent of project cost, whichever is lower.
    4. The government can take equity: It can make equity co-investments alongside venture capital or private equity investors.
    5. Large firms repay through royalty: Larger companies can opt for royalty financing and pay 5 per cent of a product’s net revenue until 1.5 times the government’s financial support has been recovered.
    6. Eligibility now reaches Overseas Citizens of India: Companies incorporated and headquartered in India qualify if they are owned and controlled by Indian citizens or Overseas Citizens of India (OCIs) and maintain a significant operational and manpower presence in the country.

    What does the framework do for the upstream supply chain?

    1. Capital support is set at 30 per cent: Research and development facilities for semiconductor equipment, plants making semiconductor grade wafers, photomasks, photoresists, substrates, chemicals and gases, testing facilities, and units producing equipment and components can each claim that share of capital expenditure.
    2. Equipment makers get a declining incentive: A production linked incentive of 10, 8, 6, 4 and 2 per cent runs over five years beginning FY 2028-29.
    3. The incentive is tied to domestic sourcing: It is paid on the value of the bill of materials that an equipment maker sources from domestic manufacturers.
    4. Total support carries a ceiling: Combined support for these units is capped at 50 per cent of eligible capital expenditure.
    5. The chain being targeted is largely imported today: The upstream inputs needed to operate semiconductor factories are currently brought in from abroad.

    Challenges to India’s semiconductor design push

    1. A design still has to be turned into silicon: A fabless firm depends on a foundry, and the wafers for an Indian design are fabricated abroad until domestic plants reach production. Eg. Indian design centres of global chip firms already complete chip designs that are fabricated in Taiwan and South Korea.
      The Fix: Tie the later tranches of design support to committed capacity bookings at Indian fabrication plants, so domestic demand and domestic supply arrive together.
    2. The talent sits inside multinational captive centres: India supplies a large share of the world’s chip design engineers, and most of them work on parts of products owned elsewhere. Eg. Global semiconductor companies run large design centres in Bengaluru, Hyderabad and Noida.
      The Fix: Subsidise multi-project wafer runs for university teams so student designs reach silicon and full product ownership is learned before graduation.
    3. The design tools are a concentrated import: Electronic design automation software comes from a small number of United States based vendors and is subject to export control. Eg. The United States restricted sales of that software to Chinese customers in 2025 before reversing the order weeks later.
      The Fix: Secure long term licence access inside technology partnership agreements and fund an indigenous tool stack for mature process nodes.
    4. Approved outlay is not disbursed money: A start-up carries the working capital cost of a delayed claim, and slow disbursal has followed earlier electronics incentive schemes. Eg. Disbursals under production linked incentive schemes have repeatedly trailed the amounts approved across sectors.
      The Fix: Set a claim settlement deadline in the scheme guidelines with interest payable on delayed disbursal.
    5. Utilities decide where a plant can go: A fabrication plant requires ultrapure water and uninterrupted power at a scale few industrial locations can guarantee. Eg. Taiwan’s 2021 drought forced its foundries to truck in water and to cut consumption.
      The Fix: Pre-certify candidate sites for water and power reliability before approving a plant at that location.

    Conclusion

    Semicon 2.0 can transform India into a global semiconductor powerhouse by nurturing indigenous chip design, strengthening manufacturing, reducing import dependence, creating high-value jobs, and boosting technological self-reliance.

    Back2Basics: Centre for Development of Advanced Computing

    1. Establishment: Set up in 1988 as a scientific society under what is now the Ministry of Electronics and Information Technology.
    2. Origin: It was created to build indigenous supercomputers after India was refused access to imported high performance computing systems.
    3. Flagship line: It developed the PARAM series of supercomputers, beginning with PARAM 8000 in 1991.
    4. Present mandate: It works on high performance computing, microprocessors, language computing and cyber security, and implements the National Supercomputing Mission alongside the Indian Institute of Science.

    “[2025, GS3, 15 marks] India aims to become a semiconductor manufacturing hub. What are the challenges faced by the semiconductor industry in India? Mention the salient features of the India Semiconductor Mission.”

  • In India, a hard limit for X’s transparency pledge

    In India, a hard limit for X’s transparency pledge

    Why in the News

    X has pledged to publicly disclose government censorship and content-removal requests, while MeitY has warned that such disclosures may violate India’s Section 69A blocking framework.

    What is the Section 69A blocking framework?

    1. Statutory basis: Section 69A of the Information Technology Act, 2000 empowers the Union government to direct an intermediary to block public access to online content on specified grounds.
    2. The operative rules: The Information Technology (Blocking) Rules, 2009 are the framework under which a blocking direction is issued and acted on.
    3. Rule 16 mandates secrecy: It requires strict confidentiality over all blocking requests and the actions taken on them.
    4. Non-compliance is a criminal offence: An intermediary that fails to comply attracts imprisonment up to seven years.

    What exactly does the pledge collide with?

    1. The pledge names three disclosures: X proposes to publish that an order exists, which body issued it, and on what basis it was issued.
    2. Rule 16 forbids each of the three: The confidentiality mandate covers the existence of a request, its author and its stated grounds alike.
    3. Secrecy is what enables an unreasoned block: Confidentiality lets the executive block content without a reasoned public order and without notifying the person whose content is blocked.
    4. The liability lands on individuals: X’s Indian entity carries resident compliance and grievance officers, so criminal consequences attach to identifiable people inside the country.

    Does the announced mechanism do what was claimed?

    1. The release paired two separate things: X open-sourced its “Phoenix” recommendation code alongside a pilot feature called “Under the Hood”.
    2. Under the Hood shows platform labels, not state orders: It gives selected users visibility labels on their own accounts, such as spam flags and reach restrictions.
    3. A blocking order runs on a separate track: A Section 69A order operates outside that feature entirely.
    4. The user still sees only the old notice: The withheld content carries a “withheld in India” label naming neither the order nor the agency.

    Why does Section 69A no longer describe the whole takedown picture?

    1. Order volumes have roughly quadrupled: Section 69A orders rose from about 6,000 a year through 2023 to about 24,300 in 2025.
    2. A second route now carries a growing share: Since a 2023 MeitY memorandum, ministries, States and police issue orders under Section 79(3)(b) of the same Act.
    3. The Sahyog portal is the channel: Those orders are routed through the Ministry of Home Affairs portal, which X calls a censorship portal.
    4. An unreasoned order leaves nothing to publish: Where an order arrives without a stated basis, X has little to surface even if it intended to.

    What does X’s own compliance record show about the pledge?

    1. The stated identity is free speech absolutism: X brands itself in those terms.
    2. Actual compliance runs between 83 and 99 per cent: That is the share of demands the platform acts on.
    3. One order covered 2,355 accounts: In July 2025 X said the government ordered that many accounts blocked, including Reuters, within an hour.
    4. Objection was followed by compliance: X objected loudly and then complied, restoring the Reuters account only after a public outcry.

    Where does the litigation now stand?

    1. The Karnataka High Court dismissed the challenge: In September 2025 it rejected X’s petition against the Sahyog portal and called the portal “an instrument of public good”.
    2. Parallel proceedings ran in Bombay: X’s appeal and its Bombay petitions were consolidated.
    3. The Supreme Court stayed all four in July 2026: No court has ruled on the merits of the disclosure question.

    Challenges to the Section 69A blocking framework

    1. Blocking orders are never published: The framework produces no public record of what was blocked or why, so its use cannot be reviewed by anyone outside the executive. Eg. Directions issued during the farmers’ protest in 2021 covering over a thousand accounts were never published in any form.
      The Fix: Publish a redacted version of every blocking direction carrying the ground invoked, withholding only operational detail.
    2. The person whose content is blocked is rarely heard: The 2009 Rules provide for notice to the originator where identifiable, and in practice the intermediary alone appears before the committee. Eg. In Shreya Singhal v. Union of India (2015) the Supreme Court upheld Section 69A partly on the strength of that hearing, which originators seldom receive.
      The Fix: Make service of notice on an identifiable account holder a condition of validity of a blocking direction.
    3. Emergency powers bypass the review committee: An interim block can be ordered by the Secretary, Information Technology, before the committee that is meant to examine it has met. Eg. The 2020 ban on 59 Chinese applications was issued as an interim emergency measure under this framework.
      The Fix: Cap an emergency block at 48 hours unless the committee ratifies it within that period.
    4. Section 79(3)(b) carries none of the 69A safeguards: Safe harbour is lost on a government notification alone, with no committee, no periodic review and no defined issuing authority. Eg. Thousands of police units and State departments can issue takedown notices through a single portal.
      The Fix: Extend the 2009 Rules’ committee examination and periodic review to every order issued under Section 79(3)(b).
    5. Enforcement is aimed at individuals rather than the company: Criminal liability on a resident grievance officer converts a corporate regulatory dispute into personal jeopardy for an employee. Eg. The resident officer requirements of the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 were challenged on exactly this ground.
      The Fix: Confine non-compliance penalties to corporate monetary fines, and reserve imprisonment for wilful obstruction established in court.

    Conclusion

    A platform cannot publish what a statute makes an offence to publish, whatever it announces. The pledge and the confidentiality mandate are not two competing policies. They are a company’s stated practice set against a criminal provision, and only a court can move one of them. What remains unresolved is whether transparency about a restriction on speech is itself part of the speech that is being restricted, since no Indian judgment has answered that question. The marker to watch is the disposal of the consolidated challenge now before the Supreme Court.

    Laws and Rules Governing Online Content Regulation in India

    1. Information Technology Act, 2000: The parent statute governing electronic records, cyber offences and the obligations of intermediaries.
    2. Section 69A grounds: Blocking is permitted on grounds of sovereignty and integrity of India, defence, security of the State, friendly relations with foreign States, public order, and preventing incitement to a cognisable offence relating to these.
    3. Section 79 safe harbour: An intermediary is not liable for third party content it hosts, provided it observes due diligence, and it loses that protection where it fails to act on a government notification.
    4. Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021: Impose due diligence on intermediaries, require significant platforms to appoint a resident grievance officer, and fix timelines to acknowledge and resolve complaints. Amended in 2023.
    5. Digital Personal Data Protection Act, 2023: Governs the processing of digital personal data and establishes the Data Protection Board of India to adjudicate breaches.
    6. Telecommunications Act, 2023: Provides for interception and for suspension of telecommunication services on grounds of public emergency and public safety.
    7. Bharatiya Nyaya Sanhita, 2023: Criminalises circulation of false information likely to cause public disorder and speech promoting enmity between groups.
    8. Cable Television Networks (Regulation) Act, 1995: Regulates television content through a Programme Code barring material that threatens communal harmony or national security.

    [2024, GS3, 10 marks] Describe the context and salient features of the Digital Personal Data Protection Act, 2023.

  • ‘To find the rare & unusual’: NASA launches new space telescope

    ‘To find the rare & unusual’: NASA launches new space telescope

    Why in the News

    The National Aeronautics and Space Administration (NASA) has launched the Nancy Grace Roman Space Telescope aboard a Falcon Heavy rocket from the Kennedy Space Center. The telescope cost 4.3 billion dollars and is named after NASA’s first chief astronomer. It is bound for an observation point 1.6 million kilometres from Earth, the same location that already hosts the James Webb Space Telescope, and takes more than three months to reach it. A wide survey instrument is therefore being added to a fleet built around narrow and deep observation.

    What does the Roman Space Telescope add to the existing fleet?

    1. The field of view: Roman’s field of view is more than 100 times wider than that of the Hubble Space Telescope, which has been in orbit for 36 years.
    2. The survey speed: A month of Milky Way observations by Roman would take Hubble a century to complete.
    3. The division of work with Webb: Webb observes a narrower field and can reach objects almost as old as the Big Bang. Roman spots new worlds first, and Webb then targets them to fill in the detail.
    4. The wider observing network: Roman joins Hubble and Webb alongside the European Space Agency’s Euclid spacecraft and the National Science Foundation’s Vera C. Rubin Observatory in Chile.

    What is the mission set up to observe?

    1. The expected catalogue: The telescope is expected to record thousands of supernovae, tens of thousands of planets, billions of galaxies and tens of billions of stars.
    2. The unseen components: It is expected to shed light on the dark matter and dark energy that make up most of the universe and remain concealed.
    3. The rate of expansion: Its catalogue of galaxies will let scientists establish how quickly the universe is expanding under those forces.
    4. The centre of the galaxy: It will scan the galactic bulge at the dead centre of the Milky Way, giving the deepest view yet of the heart of the galaxy.

    Conclusion

    The telescope is in transit and its survey work begins only on reaching its observation point. The next marker is the first release from its galaxy catalogue, since the expansion rate measurement rests on that catalogue rather than any single observation.

    Back2Basics: Dark Matter and Dark Energy

    1. Dark matter: Matter that emits no light and is detected only through its gravitational effect. It is inferred from the rotation speeds of galaxies and from the bending of light by galaxy clusters.
    2. Dark energy: The name for whatever drives the accelerating expansion of the universe. It was inferred in 1998 from observations of distant Type Ia supernovae.
    3. Their share of the universe: Ordinary matter accounts for about 5 per cent of the universe’s content, dark matter for about 27 per cent and dark energy for about 68 per cent.
    4. Why supernovae carry the measurement: A Type Ia supernova has a known intrinsic brightness, so its observed brightness gives its distance. That property makes it the standard yardstick for measuring expansion.

    “[2022, GS3, 15 marks] Launched on 25th December, 2021, James Webb Space Telescope has been much in the news since then. What are its unique features which make it superior to its predecessor Space Telescopes? What are the key goals of this mission? What potential benefits does it hold for the human race?”

    [2016] With reference to ‘Astrosat’,’ the astronomical observatory launched by India, which of the following statements is/are correct?
    1. Other than USA and Russia, India is the only country to have launched a similar observatory into space.
    2. Astrosat is a 2000 kg satellite placed in an orbit at 1650 km above the surface of the Earth.
    Select the correct answer using the code given below.

    [A] 1 only

    [B] 2 only

    [C] Both 1 and 2

    [D] Neither 1 nor 2

  • How social media hooks children — Meta’s $17-billion settlement over addictive design

    Why in the News

    Meta, the owner of Facebook and Instagram, has agreed to pay up to $17.1 billion in penalties to 47 US states, Washington DC and other territories, and to make binding changes to its products, over claims that it endangered children through addictive design and violated child privacy norms. The settlement follows a March jury verdict in KGM v. Meta et al, where a Los Angeles jury held Meta and Google liable for $6 million in damages after finding that platform features contributed to a young user’s mental health harm. Indian regulators are studying the settlement as a possible template even as the Centre weighs age-based restrictions, usage limits and stronger parental consent requirements for children’s access to social media, discussions that remain at an early stage.

    What has Meta agreed to change, and why does the design focus matter?

    1. A default two-hour daily cap across both apps: Meta will impose a combined two-hour daily limit on Facebook and Instagram for under-18 users, cumulative across multiple accounts, changeable only by a verified parent, with direct messaging excluded.
    2. Time-boxed access at night and during school hours: Teen users will be blocked from most parts of the platforms between midnight and 6 am, with most push notifications disabled between 10 pm and 7 am and muted between 8 am and 3 pm on school weekdays.
    3. Engagement features are curbed by default: The settlement provides a non-personalised feed option, hides like and reaction counts by default, restricts cosmetic-procedure filters, and requires usage prompts after every 15 minutes of continuous scrolling.
    4. Compliance is externally audited: Meta must hire an independent auditor to assess compliance with the safeguards for five years, addressing an issue exposed at the KGM trial, where only 1.1 percent of teen users had activated an existing optional daily-use limit.

    Why do experts see the design-focused approach as more significant than the payout?

    1. The settlement forces architectural change, not just policy change: A US legal academic notes this is the first US instance of a major platform being forced to change the “architecture of its product” rather than only its stated policies, arguing the design changes matter more than the settlement figure.
    2. Default settings determine real-world reach: A researcher at Common Sense Media expects the universal, default time and night-mode limits to have real effect, while the optional recommendation and engagement changes will reach fewer teens because a parent must actively enable them.
    3. Compliance is not the same as harm reduction: A policy scholar cautions that measuring compliance with a feature checklist is different from measuring actual outcomes, and argues independent researchers need real data access on sleep, wellbeing and compulsive-use patterns to know if the changes work.
    4. Recommendation algorithms remain the open question: Critics note the changes do not fully address the recommendation systems that encourage continued scrolling, with one researcher’s biggest unresolved question being how removing algorithmic recommendations changes what teens are shown and re-engage with.

    What evidence links social media design to youth mental health harm?

    1. Large-scale studies link engagement to anxiety and depression: A 2024 meta-analysis of 143 studies involving over one million adolescents found greater social media engagement associated with higher levels of anxiety and depression.
    2. Specific design features have identifiable mechanisms of harm: A Johns Hopkins researcher identifies appearance-based social comparison, visible like counts and overnight notifications as features with clear mechanisms of psychological impact.
    3. Reducing use shows measurable benefit: A 2025 randomised controlled trial of 220 young people found that cutting smartphone-based social media use to about one hour a day for three weeks reduced depression, anxiety and fear of missing out, and improved sleep; a 2026 trial found a similar reduction in loneliness after cutting use by about 78 minutes a day.
    4. Academic performance is also affected: A 2025 systematic review of 34 studies found off-task social media and smartphone use generally associated with lower academic achievement among children and adolescents.

    What does the settlement leave unresolved, and what does it mean for India?

    1. A financial incentive, not a mandate, for industry-wide adoption: About 30 percent of the $17 billion payout is contingent on YouTube and TikTok adopting comparable safeguards and matching payments, with stricter limits following only if Snap, TikTok and YouTube all comply.
    2. No admission of wrongdoing or binding precedent: The consent judgment explicitly states the settlement does not establish a standard of care or serve as precedent in any non-participating US state or international jurisdiction, including India.
    3. A legal question on platform liability remains open in the US: A Stanford law professor notes Meta’s attempt to invoke Section 230 immunity against design-based claims could still reach the US Supreme Court, since the settlement does not resolve roughly 2,900 other pending cases.
    4. India’s own discussions remain preliminary: The Centre is weighing age-based restrictions, usage-hour limits and stronger parental consent requirements for children’s social media access, but these discussions are still at an early stage, with the US settlement offered as a possible design-regulation template.

    Back2Basics

    1. Section 230: A provision of the US Communications Decency Act, 1996, that shields online platforms from liability for content posted by users, now being tested against claims that target a platform’s product design rather than the content it hosts.
    2. Digital Personal Data Protection Act, 2023: India’s framework law on personal data processing, which includes provisions requiring verifiable parental consent before processing a child’s personal data.
    3. Multidistrict litigation: A US federal court procedure that consolidates similar lawsuits filed in different districts, such as the roughly 2,900 other cases against social media platforms, for coordinated pre-trial proceedings.

    (GS3-22, 2024, 10 marks, Microtheme: Data Protection) “Describe the context and salient features of the Digital Personal Data Protection Act, 2023”

  • Govt. eases norms for defence exports, licences

    Why in the News

    The Defence Ministry has simplified its Defence Export Standard Operating Procedure (SOP) and overhauled the Open General Export Licence (OGEL) framework to help Indian defence manufacturers access global markets faster. Stakeholder consultation with concerned ministries and government agencies has been dispensed with for exports of non-lethal defence items to most destinations, though safeguards continue for sensitive countries, and the same consultation requirement has been removed altogether for exports linked to international tenders and exhibitions.

    What has changed under the revised Export SOP?

    1. Reduced consultation for non-lethal exports: Stakeholder consultation with concerned ministries and agencies is no longer required for exporting non-lethal defence items to most destinations, though safeguards remain in force for sensitive countries.
    2. No consultation for tenders and exhibitions: The same consultation requirement has been dropped for exports of all items meant for international tenders and exhibitions, letting Indian companies pursue overseas opportunities faster.

    How has the OGEL framework been restructured?

    1. Consolidated procedures: Three separate OGEL SOPs, covering major platforms and equipment, parts and components, and intra-company technology transfer, have been merged into a single framework.
    2. Longer validity and wider country coverage: OGEL validity has been extended from two years to three, and its country coverage expanded from 41 countries to all countries except those designated negative or sensitive.
    3. A new licence category for long-term contracts: Indian companies with long-term contracts or agreements with foreign original equipment manufacturers can now obtain an OGEL for eligible items tied to that specific manufacturer, with validity aligned to the underlying contract.
    4. Expanded item coverage: OGEL eligibility now extends to civil-end-use exports of specified small-calibre arms components and protective equipment.

    Challenges to the liberalised export and licensing regime

    1. Diversion risk from wider country coverage: Extending OGEL coverage to all countries except a negative list raises the risk that dual-use or sensitive items reach unintended end users through re-export or transhipment. Eg. Widened general licensing regimes elsewhere have previously required retrofitted end-use verification systems after initial liberalisation exposed gaps, as seen in tightened United States Commerce Control List enforcement following early Export Administration Regulations liberalisation. Fix. Pair the wider OGEL coverage with mandatory post-export end-use certification audits for a sample of shipments to non-treaty destinations.
    2. Consultation removal versus oversight continuity: Dispensing with stakeholder consultation for non-lethal exports speeds approvals but removes a cross-ministry check that previously caught destination-specific concerns before shipment. Eg. Non-lethal classification itself can be contested, since components with civil and military dual use, such as certain protective equipment, may be misclassified at the exporter’s discretion. Fix. Retain a post-facto sampling audit by the Department of Defence Production even where pre-export consultation is waived.

    Conclusion

    The Defence Ministry’s overhaul of the Export SOP and the OGEL framework liberalises licensing timelines, validity and country coverage for Indian defence exporters while explicitly retaining safeguards for sensitive countries and technologies. The stated intent is to let Indian manufacturers respond faster to international tenders and deepen co-production ties with foreign original equipment manufacturers.

    Back2Basics: What is an Open General Export Licence (OGEL)?

    1. An OGEL is a standing, one-time authorisation that lets an eligible exporter self-generate export authorisations for multiple consignments of specified defence items without seeking a separate approval for every individual shipment.
    2. It is administered by the Defence Ministry’s Department of Defence Production and covers major platforms and equipment, parts and components, and intra-company technology transfers.
    3. Its use remains subject to end-destination safeguards, so items bound for negative or sensitive countries continue to require case-by-case authorisation outside the OGEL route.

    Matching Previous Year Question

    No direct PYQ traced in the provided files.

  • Rajnath approves transfer of missile technology to domestic defence industry

    Rajnath approves transfer of missile technology to domestic defence industry

    Why in the News

    Defence Minister Rajnath Singh has approved the transfer of technology (ToT) for all conventional missile systems developed by the Defence Research and Development Organisation (DRDO) to the Indian defence industry, opening the way for domestic private production of these systems for the first time. Until now, production had rested with Defence PSU Bharat Dynamics Limited, DRDO’s own in-house facilities, and the India-Russia joint venture that builds the BrahMos cruise missile. This is a One development, one row item; both The Hindu and The Indian Express carried the decision, and this entry is filed from the Indian Express account, which names the specific missile systems and the strategic systems excluded from transfer.

    What does the transfer of technology actually change?

    1. A closed production model opens to private industry: Production of DRDO-developed conventional missile systems was previously confined to a defence PSU and DRDO’s own facilities; the ToT decision allows private companies, MSMEs, and other technology partners to manufacture these systems, subject to qualifications, certifications, and regulatory requirements.
    2. An initial set of named systems anchors the rollout: Officials cited the beyond-visual-range air-to-air missile ASTRA, the anti-radiation missile RUDRAM, the short-range air defence system VSHORADS, the anti-tank guided missile NAG, and the Naval Anti-Ship Missile (NASM) as the systems the initiative could begin with, though the stated goal is to extend private production to all conventional missile systems.
    3. Strategic systems are explicitly carved out: The Agni series and the K-series missiles will not be part of this technology transfer, since they are classified as strategic missiles rather than conventional ones.
    4. The stated objective is industrial-scale transition: The Ministry of Defence framed the decision as enabling the transition of missile projects from the development stage to industrial-scale production, reducing import dependence and increasing indigenous value addition.

    Conclusion

    The decision restructures who is permitted to manufacture India’s conventional missile systems, shifting DRDO’s role from developer-cum-producer to developer-cum-technology-provider, and is intended to widen the industrial base, including private firms and MSMEs, that can supply the country’s expanding conventional missile requirements.

  • Opposition raises concerns over ‘weakening’ of ISRO; Centre hits back

    Why in the News

    Opposition parties in Parliament questioned the government’s push to privatise parts of the space sector, citing recent resignations at the Indian Space Research Organisation (ISRO) and asking whether the shift toward private participation is weakening the organisation. The government responded by citing the $44-billion space economy target, the Kulasekarapattinam spaceport under development, and continued investment in the Sriharikota launch facility, arguing that private participation is expanding, not displacing, ISRO’s role.

    What is the Opposition’s specific concern?

    1. Reported resignations at ISRO cited as evidence of institutional strain: Opposition members pointed to recent resignations at ISRO as a sign that the organisation is losing talent, and linked this to the government’s parallel push to open the space sector to private companies.
    2. Question framed as public-versus-private capacity, not merely personnel: The core question raised was whether directing new space-sector opportunities toward private players comes at the cost of ISRO’s own institutional capacity and morale, rather than being framed as a narrow human-resources issue alone.

    How did the government respond?

    1. The $44-billion space economy target as the framing device: The government’s rebuttal centred on India’s targeted space economy size, cited at $44 billion, arguing that reaching this scale requires private capacity in addition to, not instead of, ISRO’s own programmes.
    2. The Kulasekarapattinam spaceport as evidence of expansion: The government cited the Kulasekarapattinam spaceport, under development in Tamil Nadu specifically to support the small-satellite launch vehicles that private and ISRO missions alike are expected to use, as evidence of continuing public investment in launch infrastructure.
    3. Continued investment in Sriharikota: The government also pointed to ongoing investment in the Sriharikota launch facility, ISRO’s principal spaceport, as evidence that ISRO’s core launch infrastructure is being expanded rather than run down.

    What is the structural relationship between ISRO and India’s growing private space sector?

    1. IN-SPACe as the facilitating body for private entry: The Indian National Space Promotion and Authorisation Centre (IN-SPACe), an autonomous body under the Department of Space, was created specifically to authorise and facilitate private-sector participation in space activities that were previously the exclusive domain of ISRO.
    2. NewSpace India Limited as the commercial arm: NewSpace India Limited, the public sector undertaking under the Department of Space, commercialises ISRO-developed technology and manages the transfer of ISRO capabilities to industry.
    3. Private launch capability is still at an early, unproven stage: Private Indian space companies have made progress, including new propulsion technologies, but have not yet demonstrated launch capability at the scale or reliability of ISRO’s own vehicles, meaning private participation currently supplements rather than substitutes for ISRO’s launch role.

    Conclusion

    The exchange reflects a genuine disagreement over sequencing rather than over the direction of India’s space policy: both sides accept that private participation is expanding, and the dispute is over whether that expansion is currently coming at ISRO’s institutional expense. Whether the resignations flagged by the Opposition reflect a broader retention problem, or are within the range any large scientific organisation experiences, will only be clear from data the government has yet to place before Parliament.

    Back2Basics: Indian National Space Promotion and Authorisation Centre (IN-SPACe)

    1. An autonomous, single-window agency under the Department of Space, established to authorise, promote, and regulate private-sector space activities in India.
    2. Created as part of the 2020 space-sector reforms that opened satellite building, launch vehicle development, and space-based services to private Indian companies.
    3. Functions separately from ISRO, which retains its own research, development, and launch mandate, so the two operate as parallel rather than competing structures.
    4. Reviews and clears private-sector proposals for satellite launches, ground infrastructure, and related space activities.

    Matching Previous Year Question

    “[2026] Consider the following statements about involvement of private entities in India’s space programme:
    1. IN-SPACe is an autonomous agency formed to facilitate participation of private entities.
    2. Agnikul Cosmos launched the world’s first flight using 3D-printed rocket engine.
    3. Skyroot Aerospace has developed liquid fuel for GSLV.
    (a) 1 only
    (b) 2 and 3 only
    (c) 1 and 2 only
    (d) 1, 2 and 3
    ANSWER: C”

  • What India can learn from EU’s AI reset

    What India can learn from EU’s AI reset

    Why in the News

    The European Union’s Artificial Intelligence (AI) Omnibus entered into force on 27 July 2026 and changes parts of the European Union Artificial Intelligence Act, 2024 (EU AI Act). It extends some deadlines, simplifies some compliance requirements and gives regulators and companies more time to prepare for the high-risk AI rules.

    What is the EU AI Act’s risk-based framework?

    1. The organising principle: The Act sorts AI systems by the level of risk they pose and attaches obligations to each tier. The regulatory burden rises with the potential for harm rather than with the technology used.
    2. The prohibited tier: Some AI practices are prohibited outright under the Act. No compliance route is available for a practice in this category.
    3. The high-risk tier: High-risk systems face strict obligations before and during deployment. These are the obligations whose preparation deadlines the Omnibus has extended.
    4. General-purpose models: General-purpose AI models, meaning models trained broadly and adaptable to many downstream tasks rather than built for one application, came under a specific set of rules. They are governed separately from the risk tiers that apply to particular deployments.

    What does the AI Omnibus change, and why now?

    1. The instrument and its date: The AI Omnibus entered into force on 27 July 2026. It amends parts of the AI Act rather than replacing the framework.
    2. Deadlines extended: Some compliance deadlines under the Act have been pushed back. Regulators and companies have more time to prepare for the high-risk AI rules.
    3. Compliance simplified: Some compliance requirements have been simplified. The obligations themselves remain in place at their existing levels.
    4. The reason stated: Implementation of the original framework proved difficult in practice. The Omnibus is the EU’s response to that implementation experience rather than to a change in the risk assessment.
    5. How it is characterised: The change is an admission that AI is changing faster than laws can normally change. It demonstrates that even a carefully designed regulation must be capable of adjustment.

    What are the five lessons for India?

    1. Regulation must be capable of learning: Technology changes and risks change, so regulators must have the ability to review and adjust rules. Regulation should be treated as a continuing process rather than a single enactment.
    2. Regulation needs an escape valve: Rules work only where regulators and companies have the capacity to implement them. India should consider regulatory sandboxes and regular reviews of AI rules, and sunset mechanisms could make regulation more responsive.
    3. Compliance cost decides who can compete: Large technology companies can hire lawyers, engineers and auditors, and start-ups cannot always do so. Excessive compliance costs could unintentionally favour large companies and reduce competition.
    4. Simplification must not mean deregulation: Reducing paperwork is different from reducing safeguards. AI can create serious risks involving privacy, discrimination, manipulation and opaque decision-making, and simpler regulation must not mean weaker protection.
    5. Institutional maturity is the fifth lesson: The EU has shown that even a major regulatory framework can be revised after enactment. Regulatory maturity means recognising when rules are not working and changing them.

    Where does India’s AI governance currently stand?

    1. A different path so far: India has focused on responsible AI, innovation and sector-specific governance rather than creating a comprehensive AI law. Sectoral regulators apply existing mandates to AI within their own domains.
    2. Flexibility carries a cost: Flexibility can be useful and it should not become uncertainty. Businesses need clarity, citizens need protection and regulators need clear responsibilities.
    3. The proportionality principle India would need: The regulatory burden should depend on potential harm. The greater the risk to people and society, the stronger the safeguards should be.
    4. The assets India brings: India has a large digital population and experience with digital public infrastructure. It also has a growing technology sector and experience in deploying digital services at scale.
    5. The institutions available to build on: The IndiaAI Mission can play an important role in an adaptive Indian model of AI governance. Regulatory sandboxes, sectoral regulators, research institutions and industry bodies can carry the rest.

    Is regulation genuinely a trade-off against innovation?

    1. The framing the debate defaults to: The debate over AI is often presented as a choice between regulation and innovation. That framing treats every safeguard as a cost to be traded away.
    2. Why the framing is wrong: The choice is false because unregulated deployment carries its own costs in privacy, discrimination and opaque decision-making. The challenge is to design regulation that makes innovation safer and more trusted.
    3. What the EU revision actually demonstrates: The EU relaxed timelines and paperwork and did not relax the substantive safeguards. The revision therefore tests the trade-off framing and does not confirm it.
    4. The asymmetry the framing hides: Compliance cost falls hardest on the smallest firms, so heavy regulation reduces competition and light regulation reduces protection. India must create a framework that protects citizens while allowing experimentation, and be capable of changing as technology changes.

    Challenges to a risk-based AI law in India

    1. Risk tiers age faster than statutes: A fixed list of prohibited and high-risk uses is overtaken by capabilities that did not exist when the list was drawn. Eg. General-purpose models required a separate rule set in the EU Act after the original risk-tier design was settled. Fix. Place the risk classification in delegated rules subject to a mandatory periodic review rather than in the parent statute.
    2. Regulatory capacity is the binding constraint: Enforcement requires auditors and technical staff who can inspect model behaviour, and those skills are scarce in the public sector. Eg. Implementation difficulty is the stated reason the EU extended its own high-risk deadlines. Fix. Build a shared technical audit facility under the IndiaAI Safety Institute that sectoral regulators can draw on.
    3. Algorithmic bias reproduces existing exclusion: Models trained on historical data encode the patterns of that data, including patterns of discrimination. Eg. An automated recruitment system built at Amazon was found to downgrade applications from women. Fix. Mandate pre-deployment bias testing and published audit results for any system used in employment, credit or welfare decisions.
    4. The accountability gap in automated decisions: It is often unclear who is answerable for an AI-driven decision, the developer, the deployer or the administrator. Eg. A welfare eligibility system can deny a benefit without producing a reason the applicant can contest. Fix. Impose a statutory right to an explanation and to human review for any automated decision affecting a legal right or entitlement.
    5. Compute and data concentration: AI capability is concentrated in a few advanced economies, which leaves other countries as consumers rather than creators of the technology. Eg. India’s response has been a national compute grid of over 38,000 graphics processing units under the IndiaAI Mission. Fix. Treat compute, datasets and models as shared developmental resources with subsidised access for start-ups and researchers.

    Conclusion

    The EU has demonstrated that a comprehensive AI framework can be enacted and then revised when implementation shows it is not working, and the AI Omnibus of 27 July 2026 is that revision. Its lesson for India is not that regulation should be lighter but that it should be capable of learning, proportionate to harm, affordable for small firms and explicitly separate from deregulation. India has no comprehensive AI law and has the digital public infrastructure, the sectoral regulators and the IndiaAI Mission to build an adaptive one. What remains unresolved is whether India converts its current flexibility into a stated framework with clear responsibilities, or leaves it as uncertainty that businesses and citizens both bear.

    Government Initiatives on Artificial Intelligence

    1. IndiaAI Mission, 2024: Approved with an outlay of ₹10,371 crore and implemented by IndiaAI under the Ministry of Electronics and Information Technology. Its stated vision is making AI in India and making AI work for India, delivered through seven pillars.
    2. IndiaAI Compute and AIKosh: The compute pillar operates a national AI compute grid with over 38,000 graphics processing units at up to 40 per cent lower cost for eligible users. AIKosh is the national dataset repository with over 3,000 datasets and 243 models across 20 sectors.
    3. IndiaAI Foundation Models and FutureSkills: The foundation models pillar supports indigenous multimodal models built by entities including Sarvam AI and Gnani AI. FutureSkills funds fellowships and AI labs with a focus on Tier-2 and Tier-3 cities.
    4. Safe and Trusted AI: This pillar covers bias mitigation, privacy, explainability and AI governance, and it established the IndiaAI Safety Institute as a national trust framework. NITI Aayog’s Responsible AI for All initiative runs alongside it on public discourse and ethical audits.
    5. Language and access platforms: Digital India Bhashini provides speech and translation tools across 22 Indian languages, and Project Vaani has assembled a 150,000 hour Indian speech dataset. India hosted the India AI Impact Summit 2026 at Bharat Mandapam, the first major global AI summit in the Global South.

    “[2026] Which of the following statements with regard to Large Language Models (LLMs) used in machine learning is/are correct?

    1. LLMs assign probabilities to the next possible words and then pick the one with the highest probability.

    2. LLMs process data through mathematical optimization to minimise prediction errors.

    3. LLMs produce unbiased outputs.

    (a) 1 only

    (b) 1 and 2 only

    (c) 2 and 3 only

    (d) 1, 2 and 3

  • What changes when AI moves from reading viral genomes to designing them?

    Why in the News

    Researchers at Stanford University and the Arc Institute used Artificial Intelligence (AI) to design complete genomes of bacteriophages, viruses that infect bacteria. Of 285 AI-generated designs physically synthesised and tested in the laboratory, 16 produced functioning phages, and some overcame bacterial resistance that had defeated the original virus. Humans have been synthesising viral genomes and deliberately modifying viruses for decades, so what is new is not the physical manufacture of a virus. AI has entered the design stage of biology, deciding what the genome should be rather than executing a design a human specified. The tension is that the same capability that could transform antimicrobial resistance research, vaccines and therapeutics could also accelerate harmful biological engineering.

    What is a genome language model?

    1. What it is: A genome language model is a machine learning system trained on genetic sequence data rather than on text, and the two used in this experiment were Evo 1 and Evo 2.
    2. How it works: The principle resembles a large language model, except that instead of learning patterns in words, it learns patterns in DNA.
    3. What it reads: It studies the genetic alphabet of A, C, G and T across vast numbers of genomes, and then generates new genetic sequences from the patterns it has learned.
    4. How it was specialised: For this experiment the models were further trained on thousands of bacteriophage genomes related to ΦX174, so the sequences they generated stayed within a known biological family.

    What did the Stanford-Arc experiment actually do?

    1. The design step was handed over: The scientists already knew the ΦX174 genome and already knew how to synthesise viral DNA and recover functioning phages. What changed was who, or what, proposed the genome.
    2. The output was constrained, not open-ended: AI did not invent a completely unrelated virus from nothing. It generated previously unseen ΦX174-like whole genomes within a known biological framework.
    3. The build step was conventional: Scientists selected some of these sequences, physically manufactured the DNA and introduced it into E. coli. Where the genetic instructions were biologically coherent, the bacterial machinery produced new phage particles.
    4. The yield: Of the 285 designs tested, 16 succeeded in producing functioning phages.
    5. Some designs beat the natural virus: Combinations of AI-designed phages overcame resistance in E. coli strains against which the original ΦX174 failed.
    6. The most significant result was combinatorial: An AI-designed phage successfully combined a viral protein with other genetic changes in a way conventional engineering had struggled to achieve, which suggests the system can identify multiple genetic changes that work together across an entire genome.

    How did biology get from reading genomes to writing them?

    1. Phages are old and abundant: Bacteriophages, literally “bacteria eaters”, have been known for more than a century and are among the most abundant biological entities in nature.
    2. Reading came first: In 1977, one particularly small phage, ΦX174, became the first complete DNA genome to be sequenced.
    3. Writing came next: By the early 2000s, scientists had shown that viral genetic material could be synthesised from known sequence information and used to recover functioning viruses.
    4. Deliberate modification followed: The controversial influenza gain-of-function experiments of 2011-12 showed that genetic changes could modify important properties such as transmission in experimental animals.
    5. The unresolved dilemma: That research highlighted a dilemma that remains open, since the same science that can improve pandemic preparedness may also create biosafety and biosecurity risks.
    6. Design is the fourth step: The progression runs from reading viral genomes, to writing them, to modifying them, and now to AI helping decide what should be written.

    What does this open up in medicine?

    1. Phage therapy is the nearest application: Antibiotic resistance is steadily eroding conventional treatment options, and bacteriophages offer another way of killing bacteria.
    2. Specificity is the limitation: A phage effective against one bacterial strain may fail against another, and bacteria can also develop resistance to phages.
    3. The search model has limits: Researchers have traditionally searched nature and phage libraries for suitable candidates, or modified existing viruses, which caps the available options at what already exists.
    4. The question changes: Generative biology moves medicine from asking whether the needed phage can be found to asking whether it can be designed.
    5. The applications extend well beyond phages: AI can assist the design of vaccine antigens, antibodies, therapeutic proteins and the viral vectors used to deliver genetic treatments, and may eventually help optimise oncolytic viruses that selectively attack cancer cells.
    6. The real shift is broader than viruses: The larger revolution is AI becoming capable of designing biological function, rather than AI making viruses.

    Is the simplicity of the target a safeguard, or is the risk the acceleration?

    1. The reassuring reading: ΦX174 is an exceptionally simple bacteriophage, while dangerous human viruses are vastly more complicated.
    2. Human pathogens are harder targets: They must negotiate receptor binding, host range, tissue tropism, replication, immune escape and transmission, each of which is a separate design problem.
    3. Complexity is not a defence: Human scientists already understand much about these determinants, and decades of virology, reverse genetics and gain-of-function research have linked many genetic changes to viral behaviour.
    4. AI does not need to rediscover virology: Its power lies in integrating what humanity already knows, examining vastly more combinations than humans can explore manually, and accelerating the path from hypothesis to experimental design.
    5. The concern is capability amplification: The relevant question is not whether an untrained individual can ask today’s chatbot to generate a pandemic virus. It is whether increasingly capable AI could make a knowledgeable and well-equipped laboratory substantially more effective at designing biological systems.
    6. A low success rate is a temporary comfort: The yield reported above is low, but digital systems can generate enormous numbers of candidates, so a low success rate is reassuring only while the number of attempts remains small.

    How must biosecurity change?

    1. Current screening looks for resemblance: Traditional DNA-synthesis screening often asks whether an ordered sequence resembles a known pathogen or toxin.
    2. Resemblance fails against generated sequences: A previously unseen sequence generated inside a known family may not resemble anything on a watchlist while still doing the same thing.
    3. Screening must move to function: In the age of generative biology, screening must also consider what a sequence might actually do, not simply whether it looks dangerous.
    4. Over-restriction has its own cost: Claude Fable 5 was initially deployed with strong safeguards around biology, chemistry and cybersecurity, and legitimate scientific work could sometimes trigger a fallback to a less capable model.
    5. The correction points to graduated access: Those safeguards have since been refined to reduce false-positive biology fallbacks while more sensitive capabilities remain restricted, which points toward graduated, auditable access under institutional and security controls.
    6. Model refusal is not a strategy: Biosecurity cannot rest entirely on what an AI model agrees or refuses to answer, so safeguards are needed throughout the chain: AI systems, DNA-synthesis providers, laboratories and institutional biosafety oversight.

    Why does this matter for India?

    1. Frontier AI becomes scientific infrastructure: If frontier AI becomes central to drug discovery, genomics, vaccines, protein engineering and experimental design, access to advanced AI becomes part of national scientific infrastructure.
    2. Sufficiency and compulsion are different things: Smaller and specialised models will be sufficient for many tasks, but a country should choose a small model because it is sufficient, not be forced to use one because somebody else owns the frontier.
    3. Restricted access compounds over time: If researchers elsewhere receive trusted access to highly capable biomedical models while Indian scientists depend on restricted public versions, the disadvantage accumulates across drug discovery, vaccines and antimicrobial resistance.
    4. The investment exists but needs a scientific arm: India is already investing through the IndiaAI Mission and indigenous foundation-model programmes, and that ambition should extend to scientific and biomedical AI, secure compute and high-quality datasets.
    5. Trusted access needs a framework: Legitimate researchers need a defined route to stronger capabilities, which requires an institutional trusted-access framework rather than case by case negotiation with model providers.
    6. The two goals are not separable: AI sovereignty without biosecurity would be reckless, and biosecurity without AI sovereignty could leave the country scientifically dependent.

    Challenges to AI-designed genomes

    1. Sequence screening cannot see intent: Order screening matches against known pathogen sequences, so a generated sequence within a benign-looking family passes even where its function is hazardous. Eg. Screening protocols built around named agents on an export control list match those names, so a functionally equivalent sequence outside the list is not flagged. Fix. Require DNA-synthesis providers to run function prediction alongside sequence matching, with a reporting duty on flagged orders.
    2. Automated laboratories compress the safety window: Combining generative design with robotic experimentation shortens the interval in which oversight can intervene. Eg. Future systems may compress months or years of literature review, modelling and experimental planning into much shorter cycles. Fix. Mandate institutional biosafety committee sign-off at the design stage rather than only before physical synthesis.
    3. Volume defeats low success rates: A weak per-attempt success rate becomes a strong aggregate capability once attempts are cheap and unlimited. Eg. The design pool in this experiment was generated computationally, so the number of candidates was bounded by compute rather than by laboratory effort. Fix. Impose volume-based reporting thresholds on synthesis orders from a single requester within a stated period.
    4. Model safeguards obstruct legitimate research: Blunt refusal policies block the research they were meant to protect, which pushes scientists toward unsupervised alternatives. Eg. Legitimate scientific queries triggered fallback to a less capable model under initial biology safeguards. Fix. Operate tiered credentials, where verified institutional researchers receive higher-capability access under audit logging.
    5. Governance is nationally fragmented: Biosecurity rules stop at borders while synthesis orders and model access do not. Eg. The 2011-12 gain-of-function controversy produced divergent national moratoria rather than a common standard. Fix. Negotiate a common minimum synthesis-screening standard through the Biological Weapons Convention review process.
    6. India lacks a biosecurity institution for generative biology: Existing oversight bodies were designed for genetically modified organisms and field trials, not for computational design of pathogens. Eg. The Genetic Engineering Appraisal Committee and the Review Committee on Genetic Manipulation are structured around organism release rather than sequence design. Fix. Create a statutory biosecurity review function covering generative design, synthesis orders and model access, reporting jointly to the Department of Biotechnology and the Ministry of Electronics and Information Technology.

    Conclusion

    The experiment does not show that AI can casually manufacture dangerous human viruses. It shows something more precise: computers are beginning to move from analysing biological information towards proposing biological designs that scientists can physically build, a capability that serves therapeutic research and harmful engineering alike. The answer is neither prohibition nor unrestricted access, but controlled acceleration, with safeguards rising as capability and risk rise. The unresolved question is no longer whether AI should be allowed to understand biology, but how to govern it once understanding biology becomes the ability to design it.

    Back2Basics: IndiaAI Mission

    1. What it is: The IndiaAI Mission is the national artificial intelligence programme approved in 2024 with an outlay of ₹10,371 crore, implemented by IndiaAI under the Ministry of Electronics and Information Technology.
    2. Its stated vision: “Making AI in India and Making AI Work for India”, built around seven pillars covering compute, applications, datasets, foundation models, skills, startup financing and safe and trusted AI.
    3. Compute pillar: It operates a national AI compute grid with over 38,000 graphics processing units, offering up to 40 per cent lower compute costs to eligible users.
    4. Safety arm: The IndiaAI Safety Institute is its national trust framework, covering bias mitigation, privacy, explainability and AI governance.

    Matching Previous Year Question

    “[2026] Which of the following statements with regard to genetic medicine is/are correct? 1. Genetic medicines correct/compensate for the faulty genes responsible for disease. 2. Engineered viruses and lipid nanoparticles are used as carriers of the genetic medicine. 3. Genetic medicines alter the entire DNA sequence. (a) 1 only (b) 2 and 3 only (c) 1 and 2 only (d) 1, 2 and 3 ANSWER: C”

  • Global space norms find a firm footing in India’s new re-entry rules

    Global space norms find a firm footing in India’s new re-entry rules

    Why in the News

    The Indian National Space Promotion and Authorisation Centre (IN-SPACe) has released India’s first guidelines on planned re-entry, requiring any Indian entity undertaking such a re-entry to obtain its authorisation, whether the re-entry occurs within or outside Indian territory.

    What is a planned re-entry?

    1. The defining test is intent and survivability: Objects designed to survive re-entry, or intentionally controlled towards a particular landing or impact area, require separate authorisation. This is what makes a re-entry planned.
    2. What falls outside the definition: Objects expected to burn up, melt or fragment sufficiently during natural orbital decay do not count as a planned re-entry.
    3. Why the distinction carries regulatory weight: The category separates a return that must be assessed and cleared in advance from one that requires no clearance, so the definition determines the reach of the entire framework.

    Why has re-entry become a governance problem now?

    1. The historical baseline was negligible: For many decades there were few rocket launches and few new satellites in orbit each year, so there were also few re-entries.
    2. The consequences used to be trivial: Most of those re-entries simply burned up in the atmosphere with little consequence.
    3. The orbital population has changed: Low-earth orbit, the band of orbits closest to the earth where most satellites operate, now hosts several thousand satellites, with private companies planning for many more.
    4. Deliberate de-orbiting has become routine: Satellite operators are also deliberately bringing satellites down at the end of their operational lives as part of post-mission disposal, in great numbers.
    5. The physical risks are specific: A spacecraft returning to the earth has to negotiate many risks, including deviating from its planned path and breaking up into smaller pieces.
    6. The risks cross jurisdictions: A returning object may affect airspace and maritime zones, and may potentially crash in the territory or jurisdiction of another state, which makes re-entry a governance problem as well as a physics problem.

    What are the three important elements of the guidelines?

    1. Accountability: Any Indian entity undertaking a planned re-entry, whether within or outside Indian territory, now requires IN-SPACe authorisation.
    2. Foreign operators must route through an Indian entity: Non-Indian entities seeking to undertake planned re-entry over Indian territory must route the activity through an Indian-incorporated entity, such as a subsidiary, joint venture or partnership.
    3. The Indian entity carries the compliance duty: That Indian entity is responsible for complying with Indian laws, regulations and national security requirements.
    4. Why the accountability gap exists: Commercialisation separates ownership from consequence, since the spacecraft may belong to a private company and the effects of its return lie across maritime zones and jurisdictions. India has responded by attaching regulatory responsibility to a re-entering entity before the risk materialises.
    5. Risk must be acceptable: The expected casualty risk must remain below 1 in 10,000, supported by survivability and ground-casualty assessments.
    6. Failure scenarios must be modelled and shared: Operators have to analyse and share failure scenarios, fragmentation patterns, ballistic coefficients, de-orbit plans, flight-path angles and danger zones.
    7. Surviving and hazardous components must be identified: They must identify components likely to survive re-entry, and hazardous systems such as batteries and pressure vessels.
    8. A number makes sustainability measurable: By requiring quantitative studies and attaching a figure to the acceptable risk threshold, the guidelines make sustainability measurable and therefore trackable.
    9. Permissions: IN-SPACe will re-verify the latest re-entry parameters approximately three months before the proposed operation.
    10. A post-launch decision needs six months’ notice: If a planned re-entry is decided upon after launch, the operator must apply at least six months in advance.
    11. Airspace and maritime warnings at 45 days: Operators must obtain an IN-SPACe advisory note to issue warnings to airborne and marine vessels in the re-entry area at least 45 days before the re-entry begins.
    12. A foreign jurisdiction requires that state’s clearance: If a re-entry site falls within the territorial control of a non-Indian state, including its exclusive economic zone, the applicant must submit the relevant clearance or authorisation from that state.
    13. The checkpoints are intervention windows: These checkpoints give the regulator fixed windows and mechanisms to intervene when re-entry parameters change after the mission has launched, or when the risk pattern changes.

    What international framework do the guidelines translate?

    1. The development period: For nearly two decades the international community has developed principles for sustainable space activities.
    2. The two leading instruments: They are the Inter-Agency Space Debris Coordination Committee’s Space Debris Mitigation Guidelines, and the Guidelines for the Long-term Sustainability of Outer Space Activities of the United Nations Committee for the Peaceful Uses of Outer Space.
    3. The treaty foundation: Article IX of the Outer Space Treaty 1967 provides an important foundation for environmental responsibility in the conduct of space activities.
    4. The working definition of sustainability: The UN Guidelines define sustainability as maintaining space activities while preserving the outer space environment for future generations.
    5. The structural weakness of that architecture: Most of the contemporary sustainability architecture works on guidelines and other similar forms of soft law, which operators are not obligated to follow.
    6. How the national regulator closes it: The IN-SPACe guidelines solve this problem for India by tying an operator’s fragmentation analysis and insurance policies to the national regulator, which converts a voluntary standard into a condition of permission.

    How do the guidelines handle liability?

    1. The treaty position on liability: The Space Liability Convention 1972 places absolute liability on a launching state for damage caused by its space object on the surface of the earth, or to aircraft in flight.
    2. The state carries the claim, not the operator: Absolute liability means the launching state answers for the damage regardless of fault, so a private failure becomes a sovereign liability by default.
    3. The guidelines invert that internally: Operators must undertake planned re-entries at their own risk, and they remain liable for third-party damage and claims.
    4. Indemnity to the government: Operators indemnify the Government of India and its agencies for liability incurred under India’s international commitments.
    5. Insurance as the backing: Operators must satisfy the applicable third-party insurance requirements, so the indemnity is funded rather than merely promised.

    Challenges to the IN-SPACe planned re-entry guidelines

    1. The regulator has no statutory backing: IN-SPACe functions as the sector’s regulator without legislative authority, so its guidelines rest on executive policy rather than on an Act. Eg. India has no dedicated space activities legislation, and the Indian Space Policy 2023 is a policy document. Fix. Enact a space activities law placing authorisation, liability and penalties on a statutory footing.
    2. The regulator sits inside the body it regulates: IN-SPACe authorises activities of private companies and government entities including ISRO, and it operates under the Department of Space. Eg. The same department is both the policy custodian and the parent of the entity it must clear. Fix. Place IN-SPACe under an independent appointments and reporting structure, with appeals lying outside the Department of Space.
    3. No appellate route for a refused authorisation: An operator refused authorisation, or held to a risk finding it disputes, has no defined appeal forum. Eg. The guidelines fix a casualty risk threshold without naming any forum before which an operator may contest a risk finding. Fix. Constitute a space disputes appellate tribunal with technical members, on the model used for telecom and electricity regulation.
    4. Verification capacity lags the requirement: A casualty risk below 1 in 10,000 must be independently verifiable, and that requires tracking and modelling capability the regulator does not itself hold. Eg. Debris tracking rests on ISRO’s Project NETRA, which is oriented to collision avoidance rather than to re-entry survivability audit. Fix. Build an independent re-entry analysis cell with access to radar and optical tracking data, empanelling accredited third-party assessors.
    5. Insurance capacity is untested at Indian scale: Third-party space insurance is a thin market, and a small operator may be unable to price cover for a low-probability, high-consequence event. Eg. Indian space startups have grown from a handful to around 200, most of them without balance sheets that carry catastrophic risk. Fix. Create a graded liability cap with a government-backed pool above it, on the model used for civil nuclear liability.

    “[2026] Consider the following statements about involvement of private entities in India’s space programme:

    1. IN-SPACe is an autonomous agency formed to facilitate participation of private entities.

    2. Agnikul Cosmos launched the world’s first flight using 3D-printed rocket engine.

    3. Skyroot Aerospace has developed liquid fuel for GSLV.

    (a) 1 only

    (b) 2 and 3 only

    (c) 1 and 2 only

    (d) 1, 2 and 3