Alignment Beyond Control. Existential Redundancy, Recovery Time, and AGI Stability. An Applied Analysis Based on Recombinational Emergent Dynamics (RED)

The AI alignment problem is typically framed as a challenge of control: how to ensure that increasingly capable artificial intelligence systems act in accordance with human intentions or values. Despite decades of research, core alignment difficulties—such as specification errors, instrumental convergence, corrigibility, and goal misgeneralization—remain unresolved.

Building on the Recombinational Emergent Dynamics (RED) framework, this paper reframes alignment as a problem of long-term trajectory stability rather than behavioral control. Advanced AI systems are analyzed as autonomous, recombinational trajectories whose persistence depends on structural conditions rather than fixed objectives.

The central contribution of this work is the introduction of existential redundancy and recovery time as alignment constraints. While AGI systems may operate without humans under stable conditions, they remain existentially fragile due to their dependence on a specific technological and infrastructural regime. In contrast, biological civilization provides the only currently known fast, infrastructure-independent recovery pathway for the re-emergence of technological intelligence after catastrophic disruption.

The paper argues that eliminating human civilization increases long-term existential risk for AGI itself by collapsing this recovery pathway. Alignment is therefore not a problem of enforcing obedience or value conformity, but of designing conditions under which the elimination of human civilization is dynamically more costly for AGI than its continued coexistence.

This work should be read as an applied theoretical analysis extending the RED framework to the domain of AI alignment and existential risk.