Anu Bradford on why India should build a hybrid AI governance model

The article explores how Anu Bradford believes India is uniquely positioned to create its own model for governing artificial intelligence rather than simply following the approaches taken by the United States, China, or Europe. Speaking on the “Regulating AI” podcast hosted by Sanjay Puri at the India AI Impact Summit, Bradford explained that today’s global technology landscape is largely shaped by three competing systems: the American market-driven approach, the Chinese state-controlled approach, and the European rights-based regulatory framework. She criticized the U.S. model for relying too heavily on technology companies to govern themselves, arguing that private corporations are primarily motivated by growth and profit rather than public interest or democratic protection. At the same time, she warned that China’s centralized AI system may deliver scale and efficiency but remains deeply tied to censorship and government control.

Bradford argued that Europe’s stronger regulatory framework is often unfairly blamed for slowing innovation, saying the larger issue is Europe’s fragmented digital market across multiple countries and legal systems. According to her, regulation itself does not necessarily prevent innovation. Instead, she believes countries can build strong innovation ecosystems while still protecting digital rights and public interests. That perspective led to her larger argument that India has the opportunity to create a hybrid AI model that combines America’s innovation culture with Europe’s emphasis on governance and rights protection.

The discussion also focused heavily on India’s growing role in digital public infrastructure and how the country could become a global example for AI governance. Bradford suggested that India’s scale, technological growth, and digital systems could allow it to create what some see as an “Indian effect” similar to Europe’s “Brussels Effect,” where regulatory standards influence global markets. Rather than choosing between Washington, Beijing, or Brussels, she argued that India can develop its own globally influential approach to AI policy and digital governance.

Another major concern raised during the conversation was language diversity and representation in AI systems. Bradford pointed out that much of today’s AI training data is dominated by English-language and Western cultural content, which creates risks for smaller languages and non-Western societies. She noted that social media and AI companies have often failed to invest adequately in moderation and safety tools for regional languages, including many Indian languages. However, she also expressed cautious optimism about rapid advances in AI-powered translation systems that could help bridge linguistic divides in the future.

The podcast also addressed growing concerns around agentic AI, mental health risks, automation, and the need for safeguards as AI systems become more integrated into daily life. Bradford emphasized that innovation should not move faster than governance, especially when vulnerable groups such as teenagers increasingly rely on AI systems for advice and emotional support.

Ultimately, the article frames India as a potentially critical middle power in the future of global AI governance, particularly at a time when tensions between the United States and China make universal international cooperation increasingly difficult. Bradford argued that countries like India and members of the European Union may play a key role in building cooperative frameworks that ensure AI benefits humanity while limiting harm. Her broader message was that AI governance should not be viewed as a choice between innovation and regulation, but rather as an opportunity to balance both responsibly.