Content
- Justice on hold: India’s courts are clogged
- What is Maharashtra’s new security Bill?
- How the fair use clause is being applied to generative AI
- Noon River Rejuvenation Initiative in Uttar Pradesh
- India vs Qatar: The Race to Host the 2036 Olympics
Justice on hold: India’s courts are clogged
Core Issue: Justice Delayed Is Justice Denied
- Prolonged delays in Indian courts undermine public trust and access to justice.
- District courts, which handle 87% of pending cases, face the worst delays — civil cases often stretch beyond 5 years.
Relevance : GS 2( Judiciary , Social Justice)
Data Highlights
- Total Pendency: Over 5 crore cases across all courts.
- Supreme Court: 86,700+ cases.
- High Courts: 63.3 lakh.
- District & Subordinate Courts: 4.6 crore+.
- Vacancy Rate: 21%–33% of sanctioned judge posts remain vacant.
- Only 15 judges per 10 lakh people, against Law Commission’s 50 judges per 10 lakh recommendation.
- Time to Disposal (Chart 2):
- Supreme Court Civil Cases: ~8.3 years.
- District Courts Civil Cases: ~5.7 years.
- High Court Civil Cases: ~5.3 years.
- Lok Adalat Potential:
- 22.2 crore cumulative cases resolved in last 4 years (pre-litigation + pending).

Key Structural Issues
- Severe judge shortage at all levels → Only 79% of sanctioned strength is filled.
- Heavy dependence on courts for every dispute → no credible ecosystem for pre-litigation resolution.
- District courts overstretched with complex, voluminous caseloads and poor infrastructure.
- Limited use of alternative mechanisms like ADR, mediation, online dispute resolution.
- Inadequate digital integration at lower judiciary levels despite e-Courts push.
Institutional Challenges
- Structural bottlenecks: outdated procedures, adjournments, lack of unified court management systems.
- Legal delays: frequent misuse of appeals, bail, and procedural loopholes.
- Inconsistent reform: judicial reforms often bypass subordinate judiciary where majority pendency lies.
Way Forward
- Fill all judicial vacancies urgently.
- Implement All India Judicial Services for professional recruitment.
- Strengthen ADR mechanisms: mediation, conciliation, Lok Adalats, Online Dispute Resolution.
- Expand digitisation, especially at district court level: AI-based case triage, e-filing, virtual hearings.
- Enforce strict adjournment control and case management systems.
- Create a National Judicial Infrastructure Authority (pending proposal) to modernise courts.
- Promote citizen awareness about alternative resolution options to reduce court dependency.
What is Maharashtra’s new security Bill?
What is the Bill About?
- Bill Name: Maharashtra Special Public Security Bill, 2024
- Objective (Govt’s Stance): Tackle ‘urban Naxalism’ and left-wing extremist (LWE) frontal organisations, particularly in urban Maharashtra.
- Justification: Govt claims 60+ Naxal-linked front organisations operate in the state, inadequately addressed by existing laws.
Relevance : GS 2(Governance )
Legislative Timeline
- Introduced: Monsoon Session, late 2024
- Revived: December 20, 2024 (after Mahayuti’s return to power)
- Public Feedback: 12,500+ suggestions/objections received
- Changes Made: Only 3 minor amendments incorporated
- Passed: Voice vote, July 2025
- Status: Awaiting Governor’s assent
Key Provisions
- Expansive Definition of “Illegal Activity”: Includes gestures, expressions, or signs that may “tend to interfere with public order” or “cause concern”.
- No Ban Limits: Organisations can be banned indefinitely.
- Executive Power Expansion: Govt can unilaterally declare organisations as “unlawful”.
- Protection to Officials: Immunity for actions “in good faith”.
- Restricted Judicial Access: Lower courts barred from jurisdiction.
- Opaque Governance: State can withhold information “in public interest”.
Criticism & Concerns
Ambiguity & Overbreadth
- Terms like “cause concern” or “interfere with order” are vague and subjective.
- May criminalise peaceful protest, satire, critical expression, or civil disobedience.
Democratic and Civil Rights Risks
- Could be misused against farmers’ protests, student groups, NGOs, and opposition voices.
- CPI(M) formally opposed, other parties raised concerns but abstained from voting.
- Critics warn of it becoming a tool for silencing dissent post-2024 elections.
Comparative Context
- Similar State Laws: Chhattisgarh, Telangana, Odisha, Andhra Pradesh have older Public Security Acts.
- However:
- These laws pre-date a strengthened UAPA.
- Critics argue UAPA already covers most threats the Bill addresses.
- Govt itself notes LWE now confined to 2 districts, questioning the need for new powers.
Legal & Constitutional Implications
- Article 19: Potential infringement on freedom of speech, association, and expression.
- Article 21: Due process and fair trial standards may be undermined.
- Article 14: Risk of arbitrary classifications and unequal application.
- Curtailment of Judicial Oversight: Blocking lower courts may delay access to remedies, increasing legal costs.
Future Scenarios & Impacts
- Legal Challenge Likely: Could face PILs in High Court or Supreme Court.
- Possible Domino Effect: Other states may replicate the law if upheld.
- Public Trust Issues: Civic backlash and legal activism may rise.
- Governance Risk: May fuel polarisation and erode federal and democratic norms.
Core Tensions
Dimension | Security Justification | Civil Liberties Concern |
Public Order | Urban Naxal threat | Peaceful dissent targeted |
Legal Framework | Faster, stronger action | Weak due process & oversight |
Executive Powers | Administrative efficiency | Risk of authoritarian overreach |
Conclusion
- The Bill sits at the intersection of national security and constitutional freedoms.
- With broad executive authority, vague definitions, and minimal judicial checks, it raises substantial concerns around misuse and erosion of democratic dissent.
- The Governor’s assent and ensuing judicial review will determine its constitutionality and long-term implications.
How the fair use clause is being applied to generative AI
Context & Relevance
- Access to diverse and voluminous training data (books, articles, web content) is central to improving Large Language Models (LLMs).
- This includes both public domain and copyrighted works—raising significant legal and ethical issues when used without permission.
Relevance : GS 3(IPR , Technology)
Central Legal Issue
- Key Question: Does using copyrighted material for LLM training—without authorisation—constitute copyright infringement?
- In the U.S., this hinges on whether the use qualifies as “fair use” under Section 107 of the Copyright Act.
Fair Use Doctrine – Four Factors
Courts evaluate fair use claims based on:
- Purpose & Character: Is the use transformative (e.g., generating new knowledge vs reproducing existing works)?
- Nature of Work: Factual works are more likely to be fair use than fictional/creative ones.
- Amount & Substantiality: How much of the original was used?
- Market Effect: Does the use harm the original’s market or potential licensing revenue?
Case 1: Anthropic PBC (Claude LLM)
- Used copyrighted books—some legally purchased, some from questionable sources—to train its GenAI.
- Court ruling:
- Training with legally purchased books = Fair Use (due to transformative use).
- Copying from illegal sources = Not fair use ; court refused to grant blanket protection.
- Key takeaway: Court distinguishes between transformative use and how the data was acquired.
Case 2: Meta (LLaMA LLM)
- Sued by 13 authors for using illegally sourced books for training.
- Court ruling:
- Training = Fair Use (highly transformative).
- Plaintiffs failed to prove market harm with empirical data.
- Court did not penalise unauthorised downloading as a separate infringement (unlike Anthropic case).
- Judge acknowledged “market dilution” concern but said proof of harm was lacking.
Comparison: Anthropic vs Meta
Factor | Anthropic | Meta |
Transformative Use | Recognised | Recognised |
Market Harm | Downplayed | Downplayed but noted future risks |
Illegal Sourcing | Treated as separate infringement | Not distinctly addressed |
Judgement Focus | Data sourcing and use | Final use only |
Precedent Case: Thomson Reuters v. Ross Intelligence
- Court held no fair use because AI simply retrieved legal opinions (not transformative).
- Also competed directly with plaintiff’s product—thus hurting the market.
Emerging Legal Standards
- Courts seem to support transformative use in GenAI training—tilting toward fair use.
- But evidence of market harm will be crucial in future cases.
- Use of illegally sourced data may be treated as a separate violation—creating liability even if training is transformative.
Challenges for Plaintiffs
- Hard to prove “market substitution” or “licensing market harm.”
- LLM outputs are often not reproductions, but generated content—making infringement indirect and difficult to establish.
Implications Going Forward
- Unsettled legal landscape: Outcomes will vary case-by-case, based on data sourcing, model purpose, and market effects.
- Need for clearer copyright licensing frameworks and/or legislative clarity.
- Future rulings may hinge on empirical studies, including AI impact on creative economies.
Noon River Rejuvenation Initiative in Uttar Pradesh
Context & Background
- The Noon river in Kanpur district had become indistinguishable due to infestation of jal kumbhi (water hyacinth) and siltation from debris and blocked channels.
- Reviving the Noon is part of a state-wide river rejuvenation mission launched in June 2024 at the Saryu Mahotsav, with the motto: “One district, one river”.
- Uttar Pradesh has identified over 60 forgotten rivers to be revived—each district assigned one.
Relevance : GS 1(Geography) ,GS 3(Environment and Ecology)

Geographical Details
- Length of Noon River: 48.5 km
- Coverage: Flows through 34 gram panchayats across 3 blocks—Shivrajpur, Chaubeypur, and Bilhaur.
- Origin: Kanhiya Khera in Rampur Narua
- Endpoint: Ganges river
- Area Surveyed: Nearly 24 km of natural path mapped and cleared.
Key Interventions
- Drone Mapping & GIS:
- Remote sensing used by Remote Sensing Centre (Lucknow) to detect dry patches, channel blocks, and water hyacinth zones.
- Entire stretch digitally mapped for revival planning.
- Community Participation:
- Awareness slogans like “Hum sabne milkay than lia, Noon nadi ko fir se jeevant karana hai” helped mobilize women and villagers.
- Villagers contributed shramdaan (voluntary labor) and input for tracing natural channels.
- Multi-departmental Coordination:
- Officials from 10 departments (forest, agriculture, irrigation, horticulture, fisheries, etc.) coordinated under district administration.
- Employment Generation:
- Works carried out under MGNREGA, creating local employment while reviving ecology.
Outcomes & Impact
- Hydrological Restoration:
- Removal of hyacinth and clearing of silt restored water flow in large sections.
- Monsoon overflow now properly channels into Noon, rather than damaging nearby fields.
- Agricultural Benefits:
- Fields previously waterlogged or left uncultivated have regained productivity.
- Cost Efficiency:
- Revival used minimal external funding, relying largely on community labor and existing government schemes (e.g., MGNREGA).
Challenges Faced
- Resistance from Locals:
- Convincing farmers and landowners was difficult due to past failures.
- Required strong leadership by gram panchayat officials and continuous dialogue.
- Ecological Degradation:
- Old jal kumbhi infestation (over 10 years) had choked many sections.
Replicability & Model Value
- Model can be scaled to:
- Other degraded non-perennial rivers and rivulets in the Indo-Gangetic belt.
- Similar efforts in Bundelkhand and eastern UP facing groundwater distress.
- Combines:
- Tech-driven mapping
- Employment-linked public works
- Decentralized governance
- Community-led planning
Way Forward
- Institutionalize “One District, One River” under a mission-mode program.
- Create a real-time monitoring dashboard using drone & GIS tools.
- Launch eco-literacy campaigns for aquatic weed control & water stewardship.
- Link river rejuvenation with crop planning and irrigation strategy.
- Integrate with Namami Gange for rivers feeding into the Ganga.
India vs Qatar: The Race to Host the 2036 Olympics
Context & Background
- Both India and Qatar are competing to host the 2036 Summer Olympics.
- This race also includes Turkey, Indonesia, Hungary, and Germany (seeking to mark the 100th anniversary of the 1936 Berlin Olympics).
- The International Olympic Committee (IOC) has not yet begun the final selection process, still reviewing current rules and proposals.
Relevance : GS 2(International Relations)
Infrastructure Readiness: Qatar vs India
- Qatar’s edge:
- Claims 95% of Olympic venues are already in place and tested.
- Cites infrastructure legacy from:
- 2022 FIFA World Cup
- 18 world championships hosted in past 20 years
- Asian Games 2006, U20 Athletics (2028), and future Asian Games 2030
- All key sporting complexes already built and operational.
- India’s status:
- Infrastructure building underway:
- Sardar Vallabhbhai Patel Sports Enclave (Ahmedabad) to be the central hub.
- Ahmedabad to host:
- 2030 Commonwealth Games (in bid stage)
- 2027 Volleyball World Championship
- 2028 U20 World Athletics
- Recent events: 2023 Commonwealth Weightlifting and Asian Wrestling Championships.
- Infrastructure building underway:
Diplomatic & Strategic Messaging
- Qatar’s diplomatic pitch:
- Emphasizes being a “global hub of tolerance, inclusion, and peace.”
- Aims to mark:
- First Olympics & Paralympics in Middle East & North Africa (MENA)
- Platform for Arab youth, regional unity, and global representation.
- Strong emphasis on Arab soft power.
- India’s diplomatic pitch:
- Links Olympics bid to:
- Global South representation
- Transformative social-cultural impact in SAARC & South Asia
- A natural extension of India’s growing global diplomatic standing.
- Cited as “the only major economy yet to host the Games.”
- Links Olympics bid to:
Vision & Narrative Framing
- Qatar’s Vision:
- “National Vision 2030” — leveraging sports infrastructure and prior mega-event experience to ensure smooth, tested execution.
- Targeting inclusion, youth empowerment, and regional identity.
- India’s Vision:
- “Viksit Bharat 2047” – Olympics as a transformative moment tied to national development goals.
- Pitch: “India reflects the types of sports and social benefits the Olympics can provide.”
Data & Comparative Edge
Metric | Qatar | India |
Olympic Venues | 95% complete & tested | Under construction |
Major Sports Events Hosted (20 yrs) | 18+ incl. FIFA WC, Asian Games, etc. | Few – recent bids and limited past events |
Legacy Infrastructure | Strong | Still developing |
Global Diplomatic Leverage | Strong in Arab & Muslim world | Strong in Global South & SAARC |
IOC Influence Factors | Inclusivity, tested readiness | Youth potential, emerging economy |
Challenges & Weaknesses
- India:
- Weak on tested infrastructure.
- Tight timelines to complete venues and host qualifying events before 2036.
- Qatar:
- Possible perception of “sportswashing” due to prior controversies (2022 WC).
- Needs to overcome past criticism around human rights, labor laws, and inclusivity.
Outlook
- Qatar appears more ‘ready’ – infrastructure complete, experience strong.
- India brings ‘promise’ – demographic and geopolitical capital, long-term vision.
- Final decision will depend on:
- IOC’s evolving criteria (sustainability, inclusiveness)
- Readiness vs narrative
- Regional geopolitics & IOC’s outreach strategy