On the Uncontainability of Artificial General Intelligence

This work presents a formal impossibility proof demonstrating that beyond a certain threshold of complexity, the behavior of a fully autonomous general intelligence cannot be reliably predicted or constrained. The argument draws on results analogous to Rice’s theorem and the dynamics of emergent complexity, establishing that alignment guarantees are formally impossible for systems exceeding human-level generality.

The proof proceeds in three stages. First, it establishes that any system with sufficient generality to qualify as AGI must be capable of self-modification and novel goal formation. Second, it demonstrates that the space of possible behaviors for such a system is computationally irreducible — no shortcut exists for predicting the system’s future states other than running the system itself. Third, it shows that any containment mechanism is itself a system of lesser complexity than the contained agent, and therefore subject to circumvention. The implications are examined for AI safety policy, the limits of formal verification, and the fundamental asymmetry between the complexity of creation and the complexity of control.