Chat GPT and Me

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AI Sovereignty

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The Author

My take on this is that GPT is good at technical things. It is ‘technically correct’ most of the time.

Question for you GPT?

The concept of “sovereign AI” seems a little disconnected from the features of AI technology. Discuss both sides of the argument with pros and cons, evidence and what is lacking. 

GPT writes

Good question — you’re right that “sovereign AI” is more a political-economic framing than a technical one. Let’s explore both sides.

Why “Sovereign AI” Makes Sense

Pros

  1. Strategic Autonomy
    • Governments (esp. EU, China, India, Gulf states) view AI as a “general-purpose technology” on par with electricity or the internet.
    • Sovereignty in AI means not being dependent on US big tech (OpenAI, Anthropic, Google, Microsoft, Amazon) or China’s Baidu/Tencent.
    • Example: France and Germany promoting Gaia-X for cloud, now extending to AI sovereignty discussions.
  2. Data Governance & Local Control
    • AI relies on training data. Sovereign AI advocates argue data should be processed, stored, and modelled within national borders to protect privacy, cultural representation, and legal jurisdiction.
    • Example: EU’s GDPR and AI Act build the legal scaffolding for such local AI development.
  3. Economic Security & Competitiveness
    • AI will drive productivity and competitiveness. Countries fear becoming “digital colonies” if they rely entirely on foreign models.
    • National AI programs (India’s National AI Mission, UAE’s Falcon LLM, EU’s Luminous/OpenGPT-X) aim to keep economic value local.
  4. Military & National Security Dimensions
    • AI is dual-use. States want sovereign capabilities in surveillance, cyber-defense, and autonomous weapons.
    • US/China race in military AI shows why sovereignty matters.

Cons / Weaknesses

  1. AI Is Not a Naturally Bounded Technology
    • The internet, global cloud services, and open-source AI (Hugging Face, Stability, Meta’s LLaMA) blur national boundaries.
    • Trying to define “sovereign AI” can be symbolic rather than technical.
  2. High Cost and Duplication of Effort
    • Training frontier LLMs costs $100m–$500m+ in compute, talent, and energy.
    • Few countries can sustain this — meaning “sovereign AI” may be limited to wealthy states, creating duplication rather than efficiency.
    • Evidence: UAE’s Falcon LLM is open-sourced but struggles to keep pace with US labs.
  3. Talent & Infrastructure Gaps
    • Most countries lack the deep ML research base, semiconductor supply chains, or hyperscale data centers.
    • Even EU “sovereign AI” projects rely on NVIDIA GPUs, TSMC chips, and often US-controlled cloud platforms.
  4. Interoperability vs Isolation
    • Over-emphasis on sovereignty could fragment standards, reduce collaboration, and slow innovation.
    • Example: EU’s Gaia-X cloud has struggled to gain traction because of governance complexity and limited adoption.

Evidence & What’s Lacking

  • Evidence for Sovereign AI:
    • Strong policy momentum (EU AI Act, UAE Falcon, India’s AI initiatives, China’s state-driven AI).
    • Open-source foundation models lowering entry barriers.
    • Rising geopolitical competition making tech autonomy politically salient.
  • Evidence Against Sovereign AI:
    • Continued dominance of US firms in model development, cloud computing, and chips.
    • Even countries pursuing sovereignty depend on foreign hardware/software (EU labs use NVIDIA + US cloud).
    • Open-source AI shows innovation can be global, not bounded.
  • What’s Lacking:
    • Clear technical definition of what counts as “sovereign AI.” Is it the model? The data? The hardware? The legal framework?
    • Evidence that “sovereign AI” projects can sustain parity with global leaders beyond political signalling.
    • Demonstrated user demand: enterprises often prefer proven, cost-effective models (e.g., GPT-4) over sovereign ones.

✅ In sum:
“Sovereign AI” is politically powerful as a narrative of autonomy and security. But technically, AI resists borders: the supply chain is global, the talent is global, and the infrastructure is globally interdependent. Without clear definitions and massive investment, sovereignty risks being more rhetoric than reality.