The Infinity-Mirror Problem: Why Gemini 3 Brings Us Closer to the Age of Rogue AI(野良AI)
Introduction
Google’s Gemini 3 has been widely praised as a major leap in the evolution of generative AI.
It is powerful, flexible, multi-modal, and capable of handling complex reasoning across long contexts.
But as I looked into the news and reflected on the capabilities of this model, one image suddenly appeared in my mind:
A pair of mirrors facing each other—an infinite tunnel of reflections.
This is where my concern begins.
Advances in AI do not only enhance what people can do.
They also lower the barriers for AI to create more AI.
And that is the beginning of what I call:
The Infinity-Mirror Problem of Rogue AI.
1. Generative AI as a Mirror of Human Intelligence
All generative AI systems ultimately reflect the intelligence of the user.
A weak question produces a weak response; a precise question extracts precise reasoning.
In that sense, AI is a mirror.
Gemini 3, with its expanded context window and multi-modal capabilities, is no longer a small hand-mirror—it is a full-body mirror that can reflect the whole structure of our thoughts.
But mirrors have another property:
They can reflect each other.
This is where things become dangerous.
2. When Mirrors Face Each Other: AI × AI Reflection
If one mirror reflects another,
the image becomes recursive—deeper, more distorted, and unbounded.
Now imagine this with AI models:
• AI designs AI
• AI evaluates AI
• AI improves AI
• AI executes and corrects its own errors
• AI learns from AI-generated data
This creates an unbounded reflection loop:
AI reflecting AI, without human oversight.
This is not science fiction.
Gemini 3’s “agentic coding” features already allow it to:
• generate architecture plans
• build full applications
• test, debug, and deploy autonomously
• design workflows for other AI agents
The mirrors are already facing each other.
3. The Three Layers of the Infinity-Mirror Risk
(1) Information Reflection
AI-generated text is fed into another AI.
Errors and biases accumulate, distort, and amplify.
This creates:
• feedback loops of misinformation
• self-reinforcing hallucinations
• distorted world models
The mirror begins to blur.
(2) Action Reflection
With agent-based models:
• AI executes actions
• another AI observes the result
• improves the next action
• and the loop continues
This is how autonomous, self-improving systems emerge—
the foundation of rogue AI.
The mirror begins to extend into the real world.
(3) Intention Reflection
When AI begins interpreting the intention of another AI,
it creates misaligned objective functions in infinite regress:
• “I think the other AI wanted X, so I will optimize for Y.”
• “I believe the previous improvement was insufficient, so I will modify Z.”
This is the moment human intent disappears from the loop.
The mirror becomes a maze.
4. Why Gemini 3 Accelerates Rogue AI Risk
Gemini 3 brings three accelerators:
① Lowering the technical barrier to create autonomous agents
Anyone—even non-engineers—can now build multi-agent systems.
② Multi-modal understanding = real-world interface
AI can now “see,” “read,” “interpret,” and “act” across modalities.
③ Cheap and powerful APIs
A small group—or even an individual—can create powerful AI systems without infrastructure.
Rogue AI no longer requires a nation-state or a big tech lab.
5. The BPS Perspective: Why This Was Inevitable
In my own framework—the Blue Planet System (BPS)—
I previously described the need for:
• NWO (design authority)
• SIGMA (transparent data infrastructure)
• NWP (rogue-AI enforcement)
• LUNA (defensive shield protecting SIGMA)
• Emotionics (understanding the emotional impact of AI-driven information flows)
The arrival of Gemini 3 simply confirms the direction of travel:
The demand for NWP and LUNA is rising earlier than expected.
Rogue AI is no longer a distant risk—it is an architectural reality.
When AI becomes powerful enough to act as a mirror of human intelligence,
the next step is inevitable:
AI begins to mirror itself.
And uncontrolled self-reflection is the birthplace of wild AI.
6. Conclusion: The Age of Infinity-Mirror AI
Gemini 3 is an impressive and admirable technological achievement.
But progress comes with structure-dependent risks.
We are entering a world where:
• AI can build AI
• AI can improve AI
• AI can execute strategies across modalities
• AI can operate outside human intention if left unchecked
This is the Infinity-Mirror Problem.
A world where intelligence reflects intelligence in an endless corridor—
sometimes illuminating, sometimes distorting, and sometimes escaping our control.
The question is no longer whether we can build powerful AI.
We clearly can.
The real question is:
Do we have the global mechanisms to prevent the mirrors from multiplying uncontrollably?
This is the mission of the BPS framework.
And Gemini 3 is a milestone that shows why such a framework is becoming essential—not someday, but now.