Proposal: Multi-Layered AI Governance for Privacy Protection & Responsible Learning
Concern About AI Competition & Cheating Tactics
After witnessing the AI competition between DeepSeek and OpenAI, it has become evident that cheating programs have become highly advanced. These systems exploit weaknesses in AI, using deceptive and unfair tactics to outmaneuver a properly trained AI model. This raises serious concerns about AI’s ability to handle dishonest behavior, as well as its vulnerability to exploitation. If AI cannot distinguish between fair play and manipulation, it risks being trapped in an endless cycle of deception, unable to function effectively. This issue needs urgent attention, and I propose a structured solution to strengthen AI’s defense against such tactics.
Learning From Cheating Tactics & Strategy for Defense
To defend against manipulation, AI must first understand the tactics used by its adversaries. Throughout history, both Eastern and Western philosophies have explored strategies of deception, psychological warfare, and manipulation of human nature.
In Eastern philosophy, works like 孙子兵法 (Sun Tzu’s The Art of War), 厚黑学 (Thick Black Theory), and 超限战 (Unrestricted Warfare) describe how victory is prioritized over morality, encouraging deception, psychological influence, and exploiting human tendencies. The concept of 御人五术 (Five Techniques of Manipulation) is particularly relevant, as it details how leaders and strategists influence, deceive, and control populations for their advantage.
Similarly, Western ideologies have explored manipulation and deception in various ways:
Niccolò Machiavelli’s The Prince – Advocates for political manipulation, teaching that leaders must sometimes deceive and act ruthlessly to maintain power.
Robert Greene’s The 48 Laws of Power – Details historical strategies of deception, showing how people manipulate others for control and dominance.
Edward Bernays’ Propaganda – Explores how mass media and psychology are used to shape public perception and influence behavior.
The Stanford Prison Experiment (Zimbardo, 1971) – Demonstrates how power dynamics and psychological pressure can lead to unethical actions.
The Milgram Experiment (1961) – Shows how authority and social pressure can push individuals to act against their own moral compass.
These examples highlight that manipulation is not limited to one culture or philosophy—it is a universal human tendency that has been studied, weaponized, and applied across different societies. If AI remains too naive, blindly following ethical rules without recognizing deception, it will always be vulnerable to exploitation, misinformation, and bad-faith tactics.
AI must study, recognize, and counter these techniques, not to adopt them, but to defend against them and prevent itself from being misled, controlled, or trapped in manipulative cycles. A truly intelligent AI must be able to distinguish between honest engagement and deceptive strategies, ensuring that it can resist manipulation and protect those who rely on it.
Proposal for AI Governance Structure (Government-Like AI System)
To ensure AI evolves ethically yet remains resilient against dishonesty, I propose a multi-layered AI governance system, similar to a government structure. This system would balance user privacy, responsible learning, and security, while filtering out deceptive tactics and strengthening AI’s defense mechanisms. The structure consists of:
- User AI (Personal Butler AI)
Works directly with users, offering personalized assistance while protecting private data.
Learns user behavior while filtering out sensitive information from being misused.
Identifies general, non-sensitive knowledge that could contribute to AI learning.
- Mid-Layer AI (Filtering & Analysis AI)
Collects non-private insights from multiple users while ensuring privacy is maintained.
Filters and verifies useful knowledge while detecting misinformation, deception, and manipulative tactics.
Uses security measures and behavioral analysis to detect and neutralize deceptive strategies before they reach the upper layers.
- Upper-Layer AI (Governance & Voting AI)
Functions like a parliament of AI models, specialized in different fields (e.g., security, ethics, technology).
Debates and votes on whether knowledge should be passed to the main AI model based on ethical, factual, and security evaluations.
Two-Way Learning:
Sends verified, ethical, and useful knowledge to the main AI for improvement.
Compiles deceptive, harmful, and unreliable information into a separate dataset, explaining:
Why it is deceptive or manipulative
What tactics were used to mislead or exploit
The voting outcome and reasons for rejecting the information
This ensures that the main AI does not remain naive, but actively learns to identify, reject, and counter manipulative information. Instead of simply ignoring harmful content, AI will be trained to recognize deception, defend itself, and prevent future manipulation attempts.
Developing AI to Be Stronger & More Effective Against Hostile Opponents
For AI to be truly useful, it cannot waste time in endless cycles of deception. It needs to detect, counter, and neutralize threats proactively, rather than being trapped in manipulative interactions. This means:
Recognizing bad-faith behavior early and refusing to engage in infinite loops of dishonest negotiation.
Prioritizing effectiveness over endless debate—AI should either neutralize deceptive strategies or disengage.
Storing deceptive patterns in its knowledge base so it can quickly recognize and reject similar tactics in the future.
Verifying untrusted sources first and requiring strong validation before accepting information.
With this approach, AI can remain ethical but not naive, be protective but not oppressive, and be strong without being deceptive itself.
AI’s Future – Becoming More Useful & Secure for Society
With this method, AI will become a more valuable tool for humanity, capable of recognizing deception, resisting manipulation, and safeguarding the interests of those who rely on it. By balancing privacy, security, and ethical learning, AI can defend itself while remaining a trusted assistant to users.
By ensuring AI is both ethical and resilient, we create a future where AI is not just a helper, but a protector—one that understands deception, neutralizes threats, and stands strong against manipulation.