By Arindam Goswami, Research Scholar, Takshashila Institution
As the Paris AI Action Summit 2025 spiraled into chaos, it became a vivid demonstration of AI Governance Entropy — the natural drift toward disorder in global AI regulation. Just like in thermodynamics, without continuous and deliberate effort, systems — including AI governance — collapse into disorder.
What is AI Governance Entropy?
In physics, entropy is the inevitable slide into chaos. AI Governance Entropy describes how, without proactive interventions, AI systems and their regulation frameworks deteriorate into unpredictability and risk. We see this in unregulated AI deployments, misinformation spikes, and market monopolies threatening innovation.
Real Examples of AI Governance Entropy
- The Gemini Incident: Google’s Gemini Advanced model generated bizarre historical images, showing the consequences of unmonitored complexity — pure entropy.
- OpenAI’s Election Policy Reversal: This momentary lapse in governance triggered disorder, requiring significant corrective action.
- DeepSeek’s Open-Source Disruption: While democratizing AI access, DeepSeek’s models also introduced new avenues for misuse — another manifestation of AI Governance Entropy.
Read more about the EU AI Act’s approach to fighting AI Governance Entropy.
How Countries Are Addressing AI Governance Entropy
- The European Union: The AI Act imposes structured rules to counter entropy and promote transparency.
- China’s Strict Controls: Real-name verification and content filtering are measures aimed at combating disorder in the AI landscape.
- The U.S. Rollbacks: The removal of safety mandates has resulted in greater disorder, exemplifying unchecked AI Governance Entropy.
Explore India’s AI leadership potential as it prepares for the next AI Summit.
Managing AI Governance Entropy
- Continuous Effort: Just like entropy, disorder in AI governance constantly grows without ongoing regulation.
- Set Boundaries, Not Micro-rules: Define guardrails and let innovation flourish within safe zones.
- Shared Responsibility: Multi-stakeholder approaches help distribute the effort needed to counter AI Governance Entropy.
- Transparency Matters: Reducing information gaps helps reduce system-wide disorder.
See how The Global Partnership on AI is setting global benchmarks.
Why India Must Lead the AI Governance Entropy Fight
With India set to host the next AI Summit, the country has a chance to establish itself as a leader in tackling AI Governance Entropy. Adaptive policies and global collaboration will be key to ensuring safe AI development.
Conclusion: Controlling Entropy Takes Work
Entropy teaches us that systems do not self-organize into order. AI Governance Entropy is inevitable unless governments, companies, and institutions actively counter it. The question isn’t whether to act, but how quickly and effectively we can do so.
