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Sovereign Data Strategies and India
Context:
In today’s interconnected world, digital infrastructure, platforms, and services form the backbone of critical sectors, from communication to commerce.
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- Recognising the significance of digital technologies, many countries have made technological sovereignty a strategic priority.
- Proponents of this approach emphasise the importance of a state’s control over digital assets, systems, and data to achieve economic, developmental, and security objectives while bolstering geopolitical influence.
- The focus lies on building or enhancing domestic capabilities and achieving self-reliance in key technological domains by reducing dependence on foreign entities or nurturing “national champions.”
India’s Vision for Technological Sovereignty
- Initiatives like Make in India and Digital India aim to establish self-reliance in critical industries and technologies.
- Data sovereignty, a key aspect of this vision, seeks to ensure state control over the personal and non-personal data of citizens.
- India’s data sovereignty strategy has two key elements:
- Restriction: Limiting foreign access to data and enforcing data localisation.
- Accumulation: Building robust domestic data ecosystems to support innovation and AI development.
India’s Data Restriction Strategy
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- Data localisation mandates require that data generated within India is stored and processed domestically.
- Cited reasons include data protection, privacy, national security, and reducing foreign surveillance.
- Regulatory measures include:
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- The Reserve Bank of India’s (RBI) localisation rules for payment data (2018).
- Bans on Chinese apps like TikTok (2020) over national security concerns.
- Requirements for VPN and cloud service providers to retain detailed customer records (2022).
- These measures aim to promote local champions and strengthen domestic data ecosystems.
Balancing Data Sovereignty and AI Ambitions
- India aspires to become a global AI powerhouse but faces constraints in computing power and access to large-scale models.
- Generative AI systems, like ChatGPT, require vast amounts of high-quality data, which makes a robust domestic data strategy essential.
- India’s approach balances data sovereignty with fostering AI innovation and global collaboration.
Regulatory Developments
- Enacted in 2023, the Digital Personal Data Protection Act (DPDPA) grants the government broad authority to restrict personal data flows while requiring compliance from entities processing data.
- Key provisions include:
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- Establishing Significant Data Fiduciaries (SDFs) with stricter obligations.
- Rule 12(4): Restrictions on transferring sensitive personal data outside India.
- Rule 14: Mandates compliance with government-specified conditions for data sharing with foreign entities.
Impact on AI Development in India
- Data localisation supports AI development by encouraging domestic data storage and processing.
- Government initiatives like the INR 100 billion AI mission focus on building AI-ready infrastructure, including data centres with high-performance computing facilities.
- Prominent developments include:
- Google’s Gemini 1.5 model, allowing local data storage.
- Investments from global players like Microsoft, Amazon Web Services, and Lenovo in AI and data centre infrastructure.
- Reliance Jio’s partnership with NVIDIA to create a “national AI infrastructure.”
Opportunities and Challenges of Data Localisation
- Opportunities:
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- Growth in India’s data centre and cloud industry.
- Creation of domestic AI ecosystems with robust infrastructure and local expertise.
- Challenges:
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- High costs of localisation may hinder small and medium enterprises from accessing data for AI innovation.
- Over-reliance on restrictive policies might impede global cooperation and innovation.
While data localisation bolsters India’s control over data, it may not always ensure seamless access or efficiency. A balanced approach combining domestic policies with global partnerships is essential to secure reliable data access and foster innovation.
