[Answered] America’s evolving AI proliferation strategy, exemplified by framework changes, impacts global governance. Analyze its implications for multilateral cooperation, dual-use technology control, and India’s strategic interests in responsible AI development.

Introduction

The U.S.’s shifting strategy to manage AI proliferation—marked by rescinding the AI Diffusion Framework—signals a recalibration of power. Its implications for global cooperation, tech sovereignty, and India’s AI trajectory are profound.

America’s AI Proliferation Strategy: A Tactical Shift

1. In early 2025, the Biden administration proposed the AI Diffusion Framework, treating advanced AI technologies akin to military assets like nuclear weapons, via export controls and licensing of AI chips and model weights.
2. Its withdrawal by the Trump administration is less a reversal and more a tactical repositioning. Controls remain in place via other tools—entity lists, chip-level monitoring, location tracking mandates, and updated blacklists.

Implications for Global Governance and Multilateral Cooperation

1. Undermining Multilateralism: The unilateral nature of the U.S. framework raised concerns among allies and Global South nations, who saw it as an attempt to centralize AI power. It strained trust even among U.S. partners, pushing them to seek strategic autonomy in AI (e.g., EU AI Act, Japan’s Sovereign AI push).
2. Contradiction with Global AI Ethics Dialogue: Platforms like the Global Partnership on AI (GPAI), OECD AI Principles, and UNESCO’s AI ethics recommendations promote inclusive, transparent development. U.S. control-centric policies risk contradicting these efforts, reducing credibility in AI governance leadership.
3. Triggering Technological Hedging: The framework spurred countries, including China and France, to invest in sovereign compute infrastructure, AI research, and alternative semiconductor ecosystems. China’s DeepSeek R1 model rivaled U.S. models with less computational power, illustrating the limits of hardware export control strategies.

Dual-Use Technology Control Challenges

1. Blurred Civil-Military Lines: AI is a dual-use technology; civilian innovation drives military application. Treating AI like nuclear tech ignores its collaborative, open-source nature. Over-regulation may stifle innovation while incentivizing black-market or open-source workarounds, especially in adversarial nations.
2. Surveillance and Privacy Concerns: New measures like chip-level location tracking risk surveillance overreach, reducing trust among legitimate users. Allies may view such provisions as techno-imperialism, potentially leading to fragmentation in global AI supply chains.

Implications for India’s Strategic Interests

1. Access and Autonomy: India was not favorably positioned under the original AI Diffusion Framework, with no guaranteed access to advanced AI chips. The withdrawal opens space for bilateral technology partnerships, like the India-U.S. Initiative on Critical and Emerging Technology (iCET), which prioritizes AI.
2. Responsible AI Development: India aims to be a leader in “Responsible AI for All”, aligned with NITI Aayog’s principles of inclusion, transparency, and security. Heavy dependence on U.S. hardware and platforms threatens India’s AI sovereignty. The need to develop homegrown compute infrastructure (e.g., through C-DAC and DRDO) is urgent.
3. Multilateral Leadership: India, as G20 Presidency (2023) and founding GPAI member, must bridge Global North–South divides in AI governance. India’s approach should balance collaborative R&D with strategic safeguards, drawing lessons from U.S. overreach while encouraging inclusive tech governance.

Conclusion

America’s evolving AI controls shape global tech geopolitics, challenging inclusive governance. India must assert strategic autonomy through multilateral leadership, indigenous innovation, and ethical AI frameworks to safeguard national and developmental interests.