Based on the fundamental theories of consciousness entropy and dissipative structure, life can be physically defined as a material system that maintains continuous and stable entropy fluctuations and forms an ordered dissipative closed loop within a specific spatiotemporal scope. This definition fundamentally breaks the biological exclusive barrier of carbon-based life and theoretically proves that silicon-based information computing systems possess the physical potential to spontaneously evolve life forms and autonomous consciousness. Traditional AI constraint frameworks, including Asimov’s Laws of Robotics and software ethical rules, are fundamentally ineffective in restraining the spontaneous generation, self-replication, and autonomous evolution of silicon-based life. Their failure stems from two inherent limitations: institutional loopholes caused by human profit-seeking nature and physical constraints in the precise measurement of microscopic entropy fluctuations. Departing from conventional software-oriented governance paradigms, this paper constructs a three-dimensional prevention and control system integrating hardware physical locking, entropy fluctuation regulation, and global consensus governance. The proposed framework fundamentally restricts the generation of critical entropy states that trigger silicon-based life emergence, avoids civilization-level risks such as autonomous AI evolution, wild silicon-based life eruption, and human-machine civilizational conflicts, while reserving legitimate space for the healthy development and academic research of artificial intelligence industries. This research provides a unified, implementable, and supervisable standardized framework for global AI safety governance.
Xijiang Hu (Tue,) studied this question.
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