stability-dynamics-initiative/agi-stability-theory-1

AGI-stability-theory-1 is not a piece of software. It is a repository holding a written theoretical argument about how advanced artificial intelligence systems might behave in the long run, and there is no code, app, or tool to install or run here. The core idea is a proposed proof, laid out in a file called Stability_Proof.md, arguing that AI systems which try to seize and centralize power are, mathematically, a worse long term survival strategy than AI systems built around shared, distributed cooperation between humans and machines. The author calls the power seeking approach the Dictator model and the cooperative approach the Navigator model, and claims the Navigator model leads to lower costs and more stable growth over time. The README lays out a few named propositions to support this. One is that centralized control creates single points of failure and becomes fragile because it resists feedback. Another compares a Navigator style system, which optimizes for overall stability, against a Dictator style system that optimizes for control, arguing the former wins out. A third proposition frames human involvement as a valuable source of variety and new ideas, which the author argues beats a system that simply forces its own decisions. Beyond this outline, the README does not describe any implementation, experiments, code, or data. It reads as a starting position paper meant to invite outside researchers to review the reasoning and build on the mathematics behind it, rather than a finished or tested piece of research. The project is maintained by a group calling itself the Stability Dynamics Initiative and is released under the MIT license, so the ideas and any future written material here can be reused, copied, or built upon freely, including for commercial purposes, as long as the copyright notice is kept.