What to Read in The Hindu Editorial( Topic and Syllabus wise)

Editorial 1: Fathoming America’s plan to manage AI proliferation

Context

The rollback of the AI Diffusion Framework seems more like a tactical adjustment than a strategic overhaul.

Introduction

The announcement by the United States to rescind its Framework for AI Diffusion—a set of export controls on Artificial Intelligence (AI) technology introduced earlier this year—has generally been welcomed as a positive move. The framework had been seen as counterproductive, both to the development of AI technologies and to diplomatic relations. However, recent developments indicate that such controls on AI are likely to continue, though they may emerge in altered or subtler forms.

Understanding the AI Diffusion Framework: Origins, Implications, and Revocation

Introduction of the Framework

• Launched by the Biden Administration:Unveiled in the final week of the administration’s tenure.
  • Known as the AI Diffusion Framework, it combined export controlsand licensing requirements for AI chips and model weights.
  • It equated AI with nuclear weaponsin terms of strategic importance and sensitivity.
• Policy Design and Scope: Countries like China and Russiafaced blanket embargoes.
  • Trusted allieswere given preferential access, while others faced restrictions.
  • Based on the idea that computational power (“compute”) determines AI capability—more compute leads to better AI models.

Strategic Logic Behind the Framework

• Control over Compute Equals Control over AI Power
  • Compute for advanced AI models has doubled nearly every 10 monthsover the last decade.
  • To preserve U.S. leadership, the framework aimed to:
    • Deny adversariesaccess to high-powered compute.
    • Retain AI developmentwithin the U.S. and its strategic allies.
  • Expansion of Pre-existing Controls
    • Previous AI hardware controlsexisted but were not comprehensive.
    • The new framework sought to:
      • Tighten regulations,
      • Create predictability,
      • Standardise licensing and export procedures.

Negative Consequences of the Framework

• Unintended Outcomes: Sweeping restrictions impacted both adversaries and partners, resulting in counterproductive effects.
  • Signalled overreachby the U.S. in dictating technology policy to other nations.
• Damaged Technology Cooperation
  • Created discomfort among allies, many of whom began:
    • Hedging against U.S. policy volatility,
    • Investing in their own AI ecosystems,
    • Pursuing strategic autonomyand technological sovereignty.
  • Mischaracterisation of AI: The framework treated AI as a military-first technology, similar to nuclear systems.
    • In reality, AI is:
      • Civilian in origin,
      • International in development,
      • Best advanced through global collaborationrather than restriction.

Counterproductive Innovation Incentives

• Motivated Workarounds
  • Restrictions spurred innovation aimed at reducing reliance on powerful compute.
  • Led to algorithmic and architectural breakthroughsin nations like China.
• Case Example: DeepSeek R1 (China)
  • Developed with limited compute resourcesyet rivals the best U.S. models.
  • Demonstrates that export controls on chipsmay not be a sustainable deterrent.

Revocation and Continuing Concerns

• Trump Administration’s Reversal
  • Rescinded the AI Diffusion Framework, recognising its strategic and diplomatic flaws.
  • Seen as positive news for countries like India, which were unfavourably placedunder the original framework.
• Enduring Strategic Mindset
  • Despite revocation, the core U.S. objective—to restrict Chinese access to advanced AI—remains unchanged.
  • Controls may persist, albeit in new or indirect formsas the AI race continues.

The possible replacement

Aspect	Details
Continued U.S. Action	Despite the rescission of the AI Diffusion Framework, the current U.S. administration is taking strong measures to curb Chinese access to AI chips.
Expansion of Export Controls	In March 2025, the U.S. expanded existing export controls and added multiple companies to its entity list (blacklist).
New Enforcement Guidelines	The administration has issued fresh guidelines aimed at tightening enforcement of AI chip export regulations.
Proposed Technological Measures	New measures under review include:

• On-chip restrictionsto monitor or limit AI chip usage.
• Hardware-level controlsto block certain applications. |
  | Legislative Developments | U.S. lawmakers have introduced bills mandating:
• Built-in location trackingon AI chips,
• To prevent illicit diversionto China, Russia, and other flagged nations.
• Shift in Strategy: These actions indicate a shift toward technological enforcementof policy goals, rather than relying solely on trade-based restrictions.

Related Concerns of Emerging U.S. AI Chip Controls

Issue	Details
Privacy and Ownership Risks	New measures—such as location tracking and on-chip monitoring—raise serious concerns around privacy, data ownership, and surveillance.
Impact on Legitimate Users	While malicious actors may find ways to bypass controls, these restrictions could inadvertently discourage legitimate and beneficial uses.
Loss of User Autonomy	Technological enforcement may undermine user autonomy and erode trust, especially in neutral or friendly countries.
Strategic Autonomy Concerns	Similar to the rescinded framework, these measures may trigger fears of lost strategic autonomyamong nations purchasing AI chips.
Global Hedging Behaviour	Both adversaries and allies may feel the need to diversify away from the U.S. AI ecosystem, and invest in independent alternatives.

Conclusion

The rescission of the AI Diffusion Framework marks a significant policy reversal, but it seems to signal a tactical adjustment rather than a fundamental change in the U.S. strategy to govern AI proliferation. If technologically-driven control measures continue to gain momentum in U.S. policy discourse and are implemented, they risk reproducing the adverse outcomes of the original framework. This would suggest that the key lessons from both the framework’s implementation and its withdrawal have not been fully absorbed. In such a scenario, the U.S. could undermine its own leadership in AI, the very objective these measures claim to safeguard.

 

Editorial 2: Vaccinating India

Context

A large number of zero-dose children are still found in poor families.

Introduction

Between 1980 and 2023, global vaccination coverage significantly improved, especially against diseases like measles, polio, and tuberculosis. A major success has been the global reduction in zero-dose children, a crucial indicator of health equity. However, despite progress, India still accounts for a large number of these children, highlighting persistent regional and socio-economic disparities in immunisation access.

Global and Indian Vaccination Trends (1980–2023)

Global Progress in Vaccination

• Between 1980 and 2023, global vaccine coverage doubledfor six major diseases:
  measles, polio, tuberculosis, diphtheria, tetanus, and pertussis.
• Significant drop in zero-dose children(children not receiving the first dose of DTP vaccine).
  • Global zero-dose rate now at 75% reduction.
  • Zero-dose children are a key indicatorof healthcare access and inequality.

Zero-Dose Children: Indian Scenario

Year	Zero-Dose Children in India	Remarks
1992	33.4%	High percentage; poor outreach
2016	10.1%	Significant progress
2019 (pre-COVID)	1.4 million	WHO baseline year
2021	2.7 million	Spike due to pandemic disruptions
2022	1.1 million	Recovery phase
2023	1.44 million	Slight increase; still above WHO target

• India ranks second globallyin the number of zero-dose children (as per The Lancet).
• India is among the 8 countriesthat together account for over 50% of global zero-dose children (~16 million).
• India’s zero-dose percentage in 2023= 2%, relatively lower due to its large birth cohort.

Key Factors Affecting Immunisation in India

Geographical Concentration: High number of zero-dose children in:

• • Large states: Uttar Pradesh, Bihar, Maharashtra, Rajasthan, Madhya Pradesh, Gujarat.
  • Northeast states: Meghalaya, Nagaland, Mizoram, Arunachal Pradesh.

 

• Sociodemographic Disparities

Group	Zero-Dose Vulnerability
Poor households	High
Mothers with low education	High
Scheduled Tribes (STs)	High
Muslim communities	High
Gender, caste gaps	Reduced over time

• Location-Based Challenges
  • Hard-to-reach tribal areas
  • Urban slumswith migrant populations
  • Areas with vaccine hesitancy, particularly among Muslim families

Meeting WHO’s IA2030 Target

Target Year	WHO Goal for India	Status (as of 2023)
2030	Halve zero-dose children (vs 2019)	Still at 2019 level (1.4 mn)

• India must reduce zero-dose children to ~0.7 millionby 2030.
• Requires sustained, targeted interventionsin:
  • Low-performing states
  • Underserved communities
  • Awareness & trust-building programs

Conclusion

India has made commendable progress in reducing zero-dose children, yet the current figures reflect a need for targeted strategies. To meet the WHO’s Immunization Agenda 2030, India must focus on vulnerable regions, combat vaccine hesitancy, and improve health infrastructure. Sustained efforts are essential to achieve universal immunisation and ensure healthcare equity for every child, regardless of geography or background.