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GS Paper II & III
International Relations & Sci-Tech
US-China AI Race and India’s Strategic Options
Xi Jinping’s Washington visit brought US–China AI cooperation into focus after their first AI talks in New York — both sides agreed to keep discussing AI risks and national-security incidents, with India’s key takeaway being the need for strong domestic AI capabilities.
Next US–China AI Meeting
Planned by November 2026
Access Risk
Brief June cut-off to top US models
India’s Stance on WAICO
Unlikely to join China-led body
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Context and Background
Why in News?
- Xi Jinping’s Washington visit (23 September) brought US–China AI cooperation into focus, following their first AI talks in New York on 20 September.
- Both sides agreed to discuss AI risks, benefits and national-security incidents, with another meeting planned by November.
- Differences remain over terminology, while for India, the key takeaway is building strong domestic AI capabilities.
Key Developments in US–China AI Relations
- The United States views AI as a global race, focusing on maintaining its technological lead, while regulation largely follows the emergence of risks.
- China emphasises human control over AI, but its approach also gives strong importance to political stability and national security.
- The US protects its technological advantage through chip export controls and supply-chain initiatives, while China promotes domestic chip self-reliance and open-weight AI models.
- In November 2024, Biden and Xi agreed that humans should retain control over nuclear-use decisions involving AI, but this understanding was not formally institutionalised.
- China has proposed an open-source AI community under BRICS, while India is unlikely to join the China-led World AI Cooperation Organization (WAICO).
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Multi-Dimensional Impact
- International Relations: Rules on frontier risk may be shaped by the two powers with most of the compute — a “G2 overlay” that leaves others as rule-takers.
- Science & Technology: Chinese open-weight models are cheap and adaptable, tempting Indian firms, while over-reliance on the American stack is also risky.
- Internal Security: Chinese models in government systems, critical infrastructure and sensitive data raise data-security concerns.
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Significance for India
- Strategic autonomy: India should maintain an independent approach and avoid becoming dependent on either the US or China for AI technology.
- Global rule-making: Participation in AI safety and incident-reporting mechanisms can help India shape global AI rules.
- National security: Decisions about using AI models in sensitive sectors can have a direct impact on India’s security and strategic interests.
- Nuclear stability: Ensuring human control over nuclear-use decisions involving AI is important for global peace and security.
Examiner tip: Frame India’s position as “multi-alignment in AI” — de-risking selectively rather than choosing a single bloc — a useful analogy to India’s broader non-alignment/strategic-autonomy tradition.
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Key Challenges for India
A brief cut-off of foreign access to top American models in June showed how quickly access can vanish — exposing India’s supply dependence on a handful of foreign AI providers.
- Exclusion risk: US-China arrangements may set norms without India at the table.
- Competing pressures: Washington wants partners’ AI ecosystems free of China, while Beijing pushes its agenda through BRICS.
- Enforcement difficulty: Stopping private firms from using cheap Chinese open-weight models is hard.
- Capability gaps: India lacks depth in compute, chips, frontier models and independent testing.
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Government Initiatives
IndiaAI Mission
Builds compute capacity, datasets and home-grown models.
India Semiconductor Mission
Develops chip manufacturing and design capacity.
Digital Personal Data Protection Act, 2023
Provides a data-handling framework.
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Way Forward
Push for Multilateral Norms
Seek a place in incident-notification arrangements on frontier AI, rather than accepting a bilateral US-China framework.
Raise Nuclear Safeguards
Make human control over nuclear-use decisions part of India’s own nuclear discourse and diplomacy.
De-Risk Selectively
Keep Chinese models out of government systems, critical infrastructure and sensitive data; require security testing and local hosting for private commercial use.
Avoid Single-Stack Dependence
Do not rely entirely on either the US or China for AI infrastructure and models.
Build at Home
Invest in compute, chips, models, datasets, talent and independent testing capacity.
Shape BRICS from Within
Insist on consensus-based, technology-neutral AI initiatives rather than a China-led agenda.
Conclusion: The US and China cannot yet agree on what to call AI, let alone how to govern it. For India, the safer path is strategic autonomy backed by capability — combining careful risk management with steady investment in compute, chips, models and talent.
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Source: The Hindu
