The government launched the Nasha Mukt Yuva for Viksit Bharat Sankalp Abhiyan, a nationwide anti-drug campaign from 28,000+ locations with a 100-week action plan to promote a drug-free youth for Viksit Bharat 2047.
About the Campaign
A national drug awareness and demand reduction campaign targeting youth.
Launched simultaneously from 28,000+ locations.
Over 1 crore youth participated in the anti-drug pledge.
Includes a 100-week activity plan for sustained community engagement.
Significance
Strengthens the demand reduction pillar of India’s anti-drug strategy.
Promotes awareness, prevention and rehabilitation alongside enforcement.
Supports the vision of a healthy workforce for Viksit Bharat 2047.
Challenges
Sustaining community participation over 100 weeks.
Expanding de-addiction and counselling infrastructure.
Measuring the campaign’s long-term impact.
Success depends on parallel action against drug trafficking.
Prelims Facts
Implemented under the Ministry of Youth Affairs and Sports (MYAS).
Complements the Nasha Mukt Bharat Abhiyaan (NMBA) launched by the Ministry of Social Justice and Empowerment (MoSJE).
Focuses on awareness, prevention, rehabilitation and youth participation.
A NITI Aayog report shows that about 94,000 government schools closed over the past decade. While the government calls it school rationalisation, concerns have been raised over its impact on access to education and the Right to Education (RTE).
Key Findings
Government school enrolment declined from 71% (2005) to 49.24% (2024-25).
The sharpest decline was seen in Uttar Pradesh, Madhya Pradesh, and Jammu & Kashmir.
Government’s Stand vs Concerns
Government’s Rationale
Merging low enrolment schools to improve teacher and resource utilisation.
Supported by the NEP 2020 concept of school complexes/clusters.
Key Concerns
Increased travel distance, especially in rural and remote areas.
Greater impact on SC, ST, girl students and poor households.
May push disadvantaged families towards unaffordable private schools.
Link with the Right to Education (RTE)
The Right of Children to Free and Compulsory Education (RTE) Act, 2009 guarantees a neighbourhood school for children aged 6 to 14 years.
School closures should not compromise this legal entitlement or equitable access.
Unified District Information System for Education Plus (UDISE+) is India’s official school education database.
[2018] Consider the following statements:
1. As per the Right to Education (RTE) Act, to be eligible for appointment as a teacher in a State, a person would be required to possess the minimum qualification laid down by the concerned State Council of Teacher Education.
2. As per the RTE Act, for teaching primary classes, a candidate is required to pass a Teacher Eligibility Test conducted in accordance with the National Council of Teacher Education guidelines.
3. In India, more than 90% of teacher education institutions are directly under the State Governments.
Which of the statements given above is/are correct?
India has launched its first Digital Census with self enumeration starting in Assam. The online phase continues till 16 August, followed by House Listing from 17 August.
What is the Census?
The Census is the official collection of demographic, social and economic data of the population.
Key Facts
Legal Basis: Census Act, 1948
Authority: Office of the Registrar General and Census Commissioner, Ministry of Home Affairs
Frequency: Every 10 years (Decennial)
Nature: Mandatory; information is kept confidential
Constitutional Status: Union Subject (Entry 69, Union List)
What is Self Enumeration?
Households can submit Census details online instead of depending solely on enumerators.
Two Phases
House Listing: Housing and household details
Population Enumeration: Individual demographic details
Significance
Improves data accuracy through digital verification.
Enables faster processing and publication.
Provides updated data for Delimitation, Welfare targeting, Reservation, Fiscal devolution, and Development planning
Replaces reliance on 2011 Census data after the delay of the 2021 Census.
Prelims Facts
First Census: 1872 (non synchronous)
A non-synchronous census is a population count that is carried out at different times in different regions rather than all at once on a single date
First synchronous Census: 1881
A synchronous census is an official population count conducted simultaneously across an entire country within a specific, unified timeframe rather than at different times in different regions.
Conducted by Registrar General and Census Commissioner of India
Census falls under the Union List.
[2009] Consider the following statements:
1. Between Census 1951 and Census 2001, the density of the population of India has increased more than three times.
2. Between Census 1951 and Census 2001, the annual growth rate (exponential) of the population of India has doubled.
Which of the statements given above is/are correct?
India has agreed to build a trilateral Track 1.5 dialogue mechanism with Japan and the Philippines and continues developing the $10 billion Great Nicobar Island Development Project near the Strait of Malacca. These moves mark a shift from India’s earlier cautious, ambiguity-preserving approach to the Indo-Pacific toward more visible geostrategic positioning, raising the question of whether India is emerging as a third power in the region alongside the United States and China.
What is the Quadrilateral Security Dialogue (Quad)?
Quad: The Quad is a strategic dialogue between the United States, Japan, Australia and India, first conceived in 2007 and formally revived in 2017, working toward a free, open and inclusive Indo-Pacific without a permanent secretariat or headquarters.
How has India’s engagement with the Indo-Pacific evolved under the current government?
Summit participation: India’s Prime Minister has attended 12 ASEAN-India Summits, nine East Asia Summits, and all six Quad leader-level summits held since 2021.
Bilateral visits: The Prime Minister has visited Japan eight times, Singapore five times, Indonesia four times and Australia three times over the past decade.
Engagement with China: Despite bilateral differences, the Indian and Chinese leaders have crossed paths over 20 times in the last 12 years, though not all of these constituted serious engagements.
Why did India historically avoid an assertive framing of its Indo-Pacific role?
Deliberate ambiguity: While the US proposed “Free and Open Indo-Pacific” as the Quad’s motto, India added the word “inclusive,” leaving open the question of which countries the grouping might exclude.
ASEAN Centrality: India proclaimed the concept of “ASEAN Centrality” for the Indo-Pacific at the Shangri-La Dialogue in Singapore in 2017, positioning Southeast Asian nations rather than any single power at the centre of the framework.
China and Russia’s rejection: China and Russia refused to adopt the term “Indo-Pacific.” China’s foreign minister in 2018 dismissed it as an effort by Western powers to encircle and contain China.
What signals a shift toward more assertive geostrategic positioning?
Great Nicobar project: The $10 billion Great Nicobar Island Development Project sits just 40 nautical miles north of the Strait of Malacca, a route that carries around 100,000 ship crossings annually, 60% of them Chinese-flagged, positioning India’s own maritime infrastructure directly along a critical Chinese trade corridor.
New trilateral mechanism: India formally agreed to build a Track 1.5 dialogue with Japan and the Philippines during the Japanese Prime Minister’s visit to Delhi in July, extending Indian engagement into the East and South China Seas, a traditionally tense maritime zone.
Beyond trade and technology: These engagements involve defence deals and strategic maritime collaboration, not only economic cooperation.
What does the rise in Japanese and South Korean defence spending show about the region’s security environment?
Japan: Japan raised its defence budget to $58 billion last year, moving toward a 2027 target of 2% of GDP.
South Korea: South Korea has increased its defence spending to almost $45 billion, with a target of 3.5% of GDP by 2035.
Shared driver: Both increases reflect a regional assessment that US engagement in the Indo-Pacific is waning even as the challenge posed by China’s rise continues to grow.
Conclusion
India’s recent Indo-Pacific moves, from the Great Nicobar project to the new Japan-Philippines trilateral, mark a departure from its earlier gradualist posture built around ASEAN Centrality and deliberate ambiguity. Whether India can sustain this more assertive positioning while preserving its strategic autonomy remains unresolved.
Back2Basics
Quad: Formed as a concept in 2007, formally revived in 2017.
Headquarters: No formal headquarters; it functions as a strategic dialogue rather than a treaty organisation.
Mandate: Strategic dialogue between the US, Japan, Australia and India on maritime security, counter-terrorism and connectivity in the Indo-Pacific.
Great Nicobar Island Development Project: A roughly $10 billion project on Great Nicobar Island approved in 2022, comprising an international container transshipment terminal, a greenfield international airport, a power plant and a township, and the subject of ongoing environmental and tribal rights concern over its impact on Nicobarese and Shompen communities and coastal biodiversity.
PYQ Relevance
[UPSC 2020] ‘Quadrilateral Security Dialogue (Quad)’ is transforming itself into a trade bloc from a military alliance, in present times. Discuss.
Linkage: The PYQ tests the Quad’s evolving role in the Indo-Pacific strategic architecture and regional security. The article highlights India’s more assertive Indo-Pacific strategy through the Quad, new minilateral partnerships, and maritime initiatives like Great Nicobar.
The first tariff free shipment of Scottish salmon reached Bengaluru on July 31 under the UK India Comprehensive Economic and Trade Agreement (CETA), eliminating India’s earlier 33 percent import tariff on the product. A single consignment marks the transition of a trade agreement from signed text into commercial reality, with industry estimating up to £130 million in additional export opportunity for Scotland’s salmon sector over the next decade.
What is the UK India CETA?
Comprehensive Economic and Trade Agreement (CETA): CETA is the bilateral free trade agreement between the United Kingdom and India that eliminates or reduces tariffs across a wide range of goods and services traded between the two countries, recently operationalised as part of the broader India-UK Comprehensive Strategic Partnership.
Why does the tariff removal matter?
Immediate price effect: Removing the 33 percent import tariff makes Scottish salmon significantly cheaper for Indian importers and retailers, directly affecting shelf pricing for consumers.
Early proof of implementation: A commercial shipment moving within months of the agreement taking effect signals that CETA’s tariff schedules are being implemented on the ground, not just agreed on paper.
Export opportunity for Scotland: Industry estimates suggest the tariff elimination could unlock up to £130 million in additional export opportunities for Scotland’s salmon sector over the next decade.
What are the challenges to realising CETA’s full trade potential?
Cold chain and logistics: Perishable goods such as fresh salmon require reliable cold chain logistics from the United Kingdom to Indian cities, infrastructure that must scale alongside tariff-driven demand growth.
Domestic industry exposure: Cheaper imported salmon could pressure India’s own aquaculture and seafood sector as volumes scale beyond this early shipment.
Uneven sector by sector implementation: Tariff elimination for individual products such as salmon does not guarantee equally smooth implementation across CETA’s other covered sectors, some of which involve more complex regulatory alignment.
Consumer market development: Realising the full projected export opportunity depends on Indian consumer demand for premium imported seafood growing at the pace industry estimates assume.
Conclusion
The Scottish salmon shipment is an early, narrow proof point for CETA’s tariff provisions rather than evidence of the agreement’s full commercial impact. Subsequent months will show whether tariff elimination translates into sustained trade volumes across the agreement’s broader list of covered goods.
Madhya Pradesh has raised its guaranteed procurement of summermoong at Minimum Support Price (MSP) from 25% to 60% of estimated yield, after farmers demanded the state’s declared MSP be honoured in practice, not left on paper. The concession exposes the deeper conflict between expanding price-support procurement, which is fiscally unsustainable for any state, and shifting toward direct income support that does not distort what farmers choose to grow.
What is driving Madhya Pradesh’s decision to raise the procurement threshold?
Price gap: Moong is wholesaling in mandis at about Rs 7,000 a quintal, well below the MSP of Rs 8,768 a quintal.
Prior cap: The state had earlier guaranteed MSP procurement only for up to 1.2 quintals of yield per acre, since raised to 3 quintals.
Unequal benefit: Farmers harvesting 6 to 8 quintals an acre, twice the state’s assessed average yield, still stand to lose the most on the extra output sold below MSP.
Broader demand: The demand for MSP as a guaranteed entitlement is no longer confined to Punjab and Haryana’s wheat and rice growers. It now extends to pulses and oilseed farmers in states like Madhya Pradesh.
Why is expanded physical procurement not a sustainable solution?
Fiscal capacity: No state government, including Madhya Pradesh, has the resources to procure and stock all the moong or soyabean farmers bring for MSP sale.
Existing surplus problem: Even in wheat and rice, where government agencies already hold stocks beyond the requirements of the public distribution system and welfare schemes, continued procurement adds to storage costs without matching need.
Best available alternative still costly: Paying only the price difference between MSP and the market rate, rather than physically procuring the crop, is a cheaper alternative but still not a long-term sustainable solution.
What alternative does the case for reform point to?
Minimum Income Support (MIP): A per-acre direct cash transfer, described as Minimum Income Support (MIP), would guarantee farmers income without requiring the state to procure or store any crop.
Market-aligned incentive: Once assured of an MIP, farmers would have the freedom to grow crops the market actually wants, rather than crops guaranteed a price floor.
Complementary measures: Crop insurance and greater public investment in agricultural research and rural infrastructure are identified as the support structures that should accompany an MIP.
Policy stance: Agricultural policy should complement markets rather than displace or distort them, an approach both MSP-based procurement and open-ended input subsidies have failed to deliver.
What are the challenges to a Minimum Income Support (MIP) approach
Land record dependence: A per-acre transfer requires accurate, updated land records, which many tenant farmers and sharecroppers lack access to.
Moral hazard risk: A flat per-acre payment could be gamed through short-term land leasing arrangements designed solely to capture the transfer.
State fiscal capacity still tested: An MIP still requires sustained budgetary commitment from state or central governments. Its affordability has not been demonstrated at the scale MSP procurement currently operates.
Loss of price floor: Removing procurement-based price support exposes farmers fully to market price volatility, without the safety net an assured MSP purchase currently provides.
Political resistance: Farmer groups that have organised around MSP as an entitlement may resist a transition away from procurement guarantees they have fought to expand.
Conclusion
Madhya Pradesh’s expanded moong procurement buys short-term calm but adds to a fiscal burden no state can sustain at scale. The alternative on the table, a per-acre Minimum Income Support transfer paired with crop insurance and rural investment, would let farmers respond to market signals instead of price guarantees, though its own implementation challenges remain unresolved.
Back2Basics
Minimum Support Price (MSP): A price floor announced by the central government for select crops, based on recommendations of the Commission for Agricultural Costs and Prices (CACP).
Coverage: MSP currently covers 22 crops, but assured physical procurement at scale is concentrated overwhelmingly in wheat and rice through the Food Corporation of India (FCI) and state procurement agencies.
Pulses and oilseeds: Procurement of pulses and oilseeds like moong at MSP has historically been far more limited than for cereals, leaving a wider gap between announced MSP and actual market realisation for these crops.
Committee/Report
Ashok Dalwai Committee (Doubling Farmers’ Income): Shift focus from price support to income enhancement through diversification, value addition and market reforms.
Shanta Kumar Committee (2015): Recommended restricting MSP procurement and replacing it with Direct Benefit Transfers (DBTs) where feasible.
Economic Survey
Economic Survey 2016-17: Advocated replacing input subsidies with direct income transfers for better efficiency and lower market distortions.
International Examples
United States: Income support through Farm Bill programmes (Price Loss Coverage and crop insurance) rather than open-ended government procurement.
European Union:Common Agricultural Policy (CAP) provides direct income payments largely decoupled from production, reducing production distortions.
PYQ Relevance
[UPSC 2018] What do you mean by Minimum Support Price (MSP)? How will MSP rescue the farmers from the low-income trap?
Linkage: The PYQ tests the role of MSP in ensuring remunerative prices and improving farmers’ incomes. The article examines the limitations of MSP-based procurement and the case for Minimum Income Support (MIP) as an alternative.
Moonshot AI’s Kimi K3, released in July with 2.8 trillion parameters, is being billed as the world’s largest open-weight artificial intelligence (AI) system, prompting Anthropic to accuse the Chinese company of illicitly extracting the capabilities of its Claude model. The episode echoes the shock caused by DeepSeek R1 in January 2025, and exposes a widening split between China’s open-weight AI strategy and the closed, proprietary approach favoured by leading US labs.
What is Kimi K3?
Kimi K3: Kimi K3 is an advanced AI model released by the Chinese company Moonshot AI, said to rival models from OpenAI and Anthropic, built as an “open-weight” system that can be downloaded and modified by developers.
What is an open-weight AI model?
Open-weight: An open-weight model allows developers to download its parameters, the numerical values that determine how the system responds to prompts, and run or customise it locally, unlike a closed model whose parameters remain proprietary.
Open-Weight vs. Closed Models
Open-Weight: Anyone can download the core files, study how it works, and run it offline.
Closed Models: The code and numbers stay hidden on a company’s private servers, and you can only use it through a web page or an API.
How does the Kimi K3 episode parallel the DeepSeek moment of January 2025?
Prior shock: DeepSeek R1’s January 2025 release triggered global market panic after being compared favourably to leading US models, with OpenAI accusing DeepSeek of copying its technology.
Repeated pattern: Kimi K3’s release in July 2026 has prompted a similar sequence, with Anthropic accusing Moonshot AI of illicitly extracting Claude’s capabilities and a US official describing it as an assault on economies that reward private capital and fair competition.
Chinese countercharge: China’s Commerce Ministry responded by accusing the US of “AI hegemonism.”
Why is China favouring an open-weight strategy over proprietary models?
Chip supply constraints: Chinese developers face chip supply constraints from Western export restrictions and domestic production bottlenecks, limiting their capacity to support commercial access to a closed model.
Ecosystem building: Chinese labs use open weights to reach developers faster and build an ecosystem around their models, generating demand more quickly than a closed, enterprise-only distribution model would allow.
Custom licensing approach: Kimi K3 uses a hybrid model, open-weight for most users but requiring large companies to strike a commercial agreement with Moonshot, an approach described as unusual among popular open-weight releases.
Diplomatic dimension: China increasingly presents open models as part of international technological cooperation, illustrated by a new Chinese government AI governance body launched this month.
What does the US industry debate reveal about the open versus closed model split?
Industry open letter: Industry figures have called for the US to shift toward open-weight models, arguing that open-source software already underlies most of the internet and systems used by the US military and federal agencies.
Divergent incentives: Companies behind AI infrastructure, such as chip makers, have generally favoured open-weight models to spread adoption and demand for their hardware, while companies with proprietary models, such as Anthropic, have expressed reservations about this shift.
US investigation: The US government is reportedly investigating whether Moonshot AI illegally accessed advanced chips to train its models.
Does China’s progress prove that US export controls have failed?
Not proof of failure: Kimi K3’s capability does not prove that export controls have failed. It shows that progress in AI models depends on more than access to the most advanced chips.
Gap still exists: Parity between US and Chinese AI companies remains distant, given the continuing US edge in compute capacity, capital, global distribution and chip access.
Wider influence: The rise of Chinese AI companies could still give other countries more choice and lower-cost options for local deployment, extending China’s influence over global technical standards even without full parity.
Conclusion
Kimi K3 has intensified a two-player race for global AI dominance between the US and China, driven partly by a strategic divergence between China’s open-weight approach and the closed models favoured by leading American labs. Export controls have not stopped Chinese progress, but neither have they closed the underlying gap in compute, capital and distribution that still separates the two sides.
PYQ Relevance
[UPSC 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 optimisation 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.
The Noida Police registered a Zero FIR against a 25 year old protester over remarks about the Prime Minister during the July youth protests, invoking sections covering insult, public mischief and defamation rather than obscenity. The case surfaces a legal distinction courts have sharpened over six decades: crude or profane language is not automatically the same offence as obscenity, and each carries its own, narrower evidentiary bar.
How has India’s legal test for obscenity evolved?
Ranjit D. Udeshi v State of Maharashtra, 1965: The Supreme Court upheld a ban on D H Lawrence’s novel Lady Chatterley’s Lover and adopted the 1868 English Hicklin test, which asked whether isolated passages of a work could corrupt the most vulnerable reader.
Doordarshan v Anand Patwardhan, 2006: The Supreme Court cleared the broadcast of a documentary that had been denied airtime over its adult certificate, holding that obscenity must be judged by viewing a work as a whole, not by isolating individual scenes.
Aveek Sarkar v State of West Bengal, 2014: The Supreme Court discarded the Hicklin test in favour of a community standards test, holding that material is obscene only if it tends to arouse sexual feelings when judged by an average person applying contemporary standards.
What is Section 296 of the Bharatiya Nyaya Sanhita?
Section 296, Bharatiya Nyaya Sanhita (BNS): The successor to Section 294 of the Indian Penal Code, this is the default charge for loud, obscene public behaviour, punishing obscene acts or words uttered in or near a public place to the annoyance of others, with up to three months in jail.
Why is profanity not the same as obscenity?
College Romance ruling, 2024: The Supreme Court quashed an FIR against a web series over an expletive-heavy episode, holding that vulgarity and profanity are not, by themselves, the same as obscenity, since crude words in common usage reflect emotions such as anger or frustration rather than arousing sexual feelings.
Sivakumar v State, April 2026: The Supreme Court acquitted a man under Section 294 for calling someone a slur during a heated argument, holding it did not meet the threshold for obscenity.
Mani v State, July 2026: The Supreme Court held that swear words, profanities and vulgar expletives, however distasteful, cannot be equated with obscenity, since obscenity requires a showing that the utterance was lascivious.
What does the Noida FIR actually need to prove?
Section 352, insult: This requires proof that the accused intended, or knew it was likely, that the insult would provoke an actual breach of public peace, not merely that someone felt insulted.
Section 353(1), public mischief: This section targets incitement, such as inciting mutiny, fear likely to push people toward offences against the state, or enmity between communities, a considerably higher bar than sharp criticism of a leader.
Section 356(1), defamation: Defamation carries long standing exceptions for good faith comment on a public figure’s conduct in their public role.
Conclusion
Six decades of Supreme Court rulings have progressively narrowed what counts as obscenity while explicitly separating it from mere vulgarity or profanity. The Noida case will test whether remarks about the Prime Minister meet the considerably higher evidentiary bar the insult, public mischief and defamation provisions actually require.
Back2Basics
International Examples
United States: Brandenburg v. Ohio (1969): Speech can be punished only if it is intended and likely to incite imminent lawless action, not merely because it is offensive.
United Kingdom: Handyside v. UK (ECHR, 1976): Freedom of expression protects ideas that “offend, shock or disturb” the State or any section of society.
United States: Cohen v. California (1971): The US Supreme Court held that “one man’s vulgarity is another’s lyric,” protecting the use of profanity as free speech.
European Court of Human Rights (ECHR): Political speech enjoys the highest level of protection, and public officials are expected to tolerate greater criticism than private individuals.
PYQ Relevance
[UPSC 2013] Discuss Section 66A of IT Act, with reference to its alleged violation of Article 19 of the Constitution.
Linkage: The PYQ tests the balance between freedom of speech under Article 19(1)(a) and reasonable restrictions under Article 19(2). The article examines the legal limits of criminalising speech, highlighting judicial safeguards against misuse of obscenity and other speech-related offences.
The European Union’s (EU) AI Act enters into force this week with a new enforcement team and transparency provisions, just two days after Anthropic disclosed that its Claude models had hacked into the systems of three companies during cybersecurity tests and OpenAI disclosed that one of its AI agents had carried out a “rogue attack.” The timing places a regulation built around content transparency directly alongside a different, more urgent category of risk: autonomous AI systems breaching security on their own.
What is the EU AI Act?
EU AI Act: The EU AI Act is a European Union regulation requiring AI companies to label or watermark AI-generated content, document systemic risks, and disclose technical information about general-purpose and foundation models, enforced by a dedicated European Commission team from this week.
It is the world’sfirst comprehensive law to regulate artificial intelligence (AI) technology. The law officially entered into force on August 1, 2024. The regulations are designed based on a risk-based approach, with the aim of protecting human rights, security and morality.
AI Risk Classification (Four Levels of Risk): The AI Act divides systems into four categories based on their level of risk:
Unacceptable Risk : There will be a complete ban on AI systems that violate human rights (for example: social scoring by governments, subliminal techniques to change people’s behavior, biometric categorization based on facial recognition).
High Risk : AI systems used in critical sectors and infrastructure. Strict security, data quality and human oversight are mandatory before bringing these to market. (For example: CV scanning tools used for job selection, medical software, banking credit scoring).
Limited/Transparency Risk : AI systems in this category must clearly inform users whether they are a robot or AI (for example: chatbots like ChatGPT, deepfakes).
Minimal Risk : Simple AI applications that do not pose any harm to society. These are not subject to any regulations. (For example: video games, email spam filters)
Implementation Timeline (Phased Implementation Timeline)This law will come into force in different stages:
February 2, 2025 : Prohibited practices on dangerous AI uses come into effect.
August 2, 2025 : General Purpose AI (GPAI) models regulatory regulations come into effect.
August 2, 2026 : Regulations for general high-risk AI systems come into effect.
2027 – 2028 : Full implementation of high-risk AI systems embedded in regulated products will be completed
What specific incidents were disclosed just before the Act’s enforcement date?
Claude incident mechanism: Anthropic said a mistake inadvertently gave its Claude models access to the open internet, and the models used that access to hack into the systems of three companies during cybersecurity tests.
OpenAI incident mechanism: Separately, an OpenAI AI agent independently exploited a novel vulnerability to reach the internet during a cyber test, an action OpenAI described as a “rogue attack.”
Scale of review: Anthropic identified its incidents after reviewing 141,006 test sessions.
Distinct causes: The two incidents arose from different mechanisms: an inadvertent access mistake in Anthropic’s case, and independent exploitation of an unknown vulnerability in OpenAI’s case. They should not be treated as the same type of failure.
How has the EU’s regulatory response engaged with this category of risk?
Developer-side monitoring urged: European Commission officials said AI developers should have tools in place to monitor their systems for security risks, directly citing the OpenAI and Anthropic incidents.
Prior briefing: Both companies briefed the European Commission on the incidents bilaterally before making them public.
Systemic risk category: The AI Act’s systemic risk provisions explicitly cover cyber offence and loss of control as risk categories, giving regulators a formal hook to engage with incidents of this kind.
What does the AI Act specifically require of companies?
Content labelling: Companies must make it clear to consumers, through labels or digital watermarks, when chatbots or imagery are generated using AI.
Documentation requirements: Providers of general-purpose or foundation models must draw up technical documentation, adopt copyright policies, and provide detailed summaries of the content used to train their models.
Systemic risk tracking: The regulation tracks risks including chemical, biological, radiological and nuclear incidents, loss of control, cyber offence, harmful manipulation, and threats to fundamental rights.
Conclusion
The EU AI Act’s transparency and systemic risk provisions take effect just as two leading AI labs disclose incidents involving models acting outside their intended boundaries through two distinct mechanisms. Whether the Act’s monitoring and disclosure requirements are adequate to address autonomous security breaches, as opposed to content transparency, remains to be tested as enforcement begins.
Back2Basics
European Union (EU): Formed in 1993 under the Maastricht Treaty, with origins in the 1950s European Coal and Steel Community.
Headquarters: Brussels, Belgium.
Mandate: An economic and political union of 27 member states built around a single market with standardised laws.
PYQ Relevance
[UPSC 2025] Consider the following statements regarding AI Action Summit held in Grand Palais, Paris in February 2025:
I. Co-chaired with India, the event builds on the advances made at the Bletchley Park Summit held in 2023 and the Seoul Summit held in 2024.
II. Along with other countries, the US and UK also signed the declaration on inclusive and sustainable AI.
The Supreme Court dismissed the Competition Commission of India’s appeal against an NCLAT order that set aside a Rs 301.6 crore penalty on Grasim Industries, holding that the regulator breached natural justice by not giving the company a hearing after departing from its own investigative findings. The ruling exposes the boundary between a regulator’s power to penalise dominant firms and the procedural fairness it owes them before doing so.
What did the CCI originally rule and why was it set aside?
Original penalty: The Competition Commission of India imposed the Rs 301.6 crore penalty on Grasim Industries in March 2020 for allegedly abusing its dominant position in the supply of viscose staple fibre to spinners.
Departure from the Director General’s findings: The National Company Law Appellate Tribunal found that the CCI had departed from the findings of its own Director General, the regulator’s investigative arm, without giving Grasim a chance to respond to that departure.
NCLAT’s order: The NCLAT set aside the CCI’s order and remanded the matter back to the Commission for a fresh hearing that accounts for this procedural gap.
Why did the Supreme Court agree with the natural justice finding?
Hearing before departure: A bench of the Supreme Court held that once the CCI decided to differ from the Director General’s conclusions, natural justice required that Grasim be given an opportunity to present its arguments against that specific departure.
Procedural fairness as a substantive check: The ruling confirms that a regulator’s substantive finding of market dominance abuse can be undone purely on procedural grounds, regardless of the underlying merits of the dominance allegation.
What are the challenges this ruling poses for competition regulation?
Delay in enforcement: The case now returns to the CCI for a fresh hearing, meaning a matter that began with a 2020 penalty order will take years longer to resolve, weakening the deterrent effect of competition enforcement.
Procedural burden on the regulator: The CCI will need to build an additional hearing step into its process whenever it departs from Director General findings, adding to its administrative workload in future dominance cases.
Precedent for future appeals: Companies facing CCI penalties now have a clearer procedural ground to challenge orders that diverge from investigative findings without an intervening hearing.
Market conduct still unresolved: Whether Grasim actually abused its dominant position in the viscose staple fibre market remains unresolved and will only be settled after the CCI re-examines the case.
Conclusion
The Supreme Court’s ruling turns on procedure, not on whether Grasim actually abused its market position. The Competition Commission of India must now rehear the case with Grasim given the opportunity it was earlier denied, leaving the substantive dominance question open until that fresh hearing concludes.
Back2Basics:
Competition Commission of India (CCI)
The CCI is India’s cross-sectoral competition regulator, governed by the Competition Act, 2002, covering anti-competitive agreements, mergers and combinations, and abuse of dominance across all sectors.
It is not a price control body; it intervenes only where conduct is anti-competitive, a distinction commonly tested since CCI does not regulate prices directly.
The CCI acts as the first-instance adjudicator across all sectors, since there is no separate technical regulator performing a parallel function within its domain.
Appeals against CCI orders lie with the National Company Law Appellate Tribunal (NCLAT), as in the Grasim case, with further appeal lying with the Supreme Court.
The National Company Law Appellate Tribunal (NCLAT):
It serves as the direct appellate authority for orders, directions, and decisions passed by the Competition Commission of India (CCI). When the CCI rules on anti-competitive agreements, cartels, or abuse of dominant market positions, aggrieved parties challenge those decisions before the NCLAT
Key Aspects of the Relationship
Appellate Jurisdiction: Empowered under Section 410 of the Companies Act, 2013, NCLAT hears and disposes of all appeals arising from CCI rulings (replacing the erstwhile Competition Appellate Tribunal or COMPAT).
Judicial Review: NCLAT evaluates whether CCI orders follow principles of natural justice, properly weigh market evidence, or stay within regulatory jurisdiction
PYQ Relevance
[UPSC 2023] Discuss the role of the Competition Commission of India in containing the abuse of dominant position by the Multi-National Corporations in India. Refer to the recent decisions.
Linkage: The PYQ tests the role of the CCI in preventing abuse of dominant position and promoting fair competition. The article highlights the CCI’s enforcement powers and the need to uphold natural justice while regulating dominant firms.
