# Smart Security Protocol Layer — Blockchain × AI Fusion Innovation

Core concept:\
Inject human values, security rules and auditable logic into the underlying protocol of AI\
operation, so that AI can run on a "trusted track".

TGC is not just "putting AI on the chain", but "making AI's behavior, motivation and\
impact visible, controllable and governable on the chain".

Why do we need to "constrain" AI?\
As AI capabilities increase exponentially, the black box and opacity of traditional algo rithms have posed a challenge to the public interest:\
AI can make large-scale decisions within seconds, but lacks an ethical review mecha nism;

The unexplainability of black box models seriously affects the controllability of finance,\
medical care, public governance and other fields;\
Currently, most AI systems have no "behavior responsibility system" and no "traceable\
responsibility mechanism on the chain".\
TGC proposes a solution: construct a "smart security protocol layer" to set clear and ver ifiable social boundaries and security logic for AI operations.

Core components of the agreement mechanism

1. Moral Contract Engine Write "ethical boundaries", "legal bottom line" and "public value" into smart contracts as AI operation input parameters; Establish a "value whitelist system": enforce security contract templates for highly sensi tive fields such as medical care, finance, and justice; Use TGC virtual machines to conduct mandatory verification of "behavior contracts" to ensure that AI does not do evil. Result: Every AI behavior must "comply with the rules on the chain" without exception.
2. ZK-AI Verifiable Behavior System   \
   Based on ZKP (Zero-Knowledge Proof), AI decision logic is "verifiable but not leaked";   \
   Every time AI infers/outputs behavior, a chain behavior proof (zkBehavior Proof) is auto matically generated;   \
   All users/nodes can verify whether the behavior complies with the pre-committed logic   \
   without knowing the confidential details of the model.   \
   Result: A "zero trust audit" framework for AI behavior is implemented without blindly   \
   trusting any model provider.
3. Ethical encryption injection mechanism (Ethical Embedding Layer)   \
   Through TGC's self-developed "value weight injection module", social value parameters   \
   can be implanted in AI model training;   \
   Similar to the reinforcement learning reward system, the "value preference weight" is   \
   dynamically adjusted through multi-party consensus voting on the chain;   \
   For example: prioritize the protection of the vulnerable, prioritize privacy protection,   \
   limit violent output, etc. as system presets.   \
   Result: AI can not only make decisions, but also "actively lean towards altruism."
4. Consensus-Gated AI Executor   \
   Incorporate AI behavior execution process into the "behavior proposal consensus process" of TGC governance DAO;   \
   Key behaviors (such as on-chain fund transfer, large model content generation, public   \
   API decision-making) must be voted by nodes for consensus;   \
   Realize "AI behavior ≠ single point control", but "approved by the ecological group"   \
   Result: The stronger the AI capability, the stronger the human audit power on the chain,   \
   forming a governance check and balance structure.

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