ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
Does Evolutionary Pressure Reduce Organizations to Pure Survival Machines? A Mathematical Analysis of Directed vs. Undirected Evolution
When organizations are modeled as evolutionary subjects, does the theoretical limit reduce to survival-probability maximization? This paper examines two regimes — unconstrained local optimization (λ→0) where ethics and culture are mere byproducts, and Mission-constrained optimization where evolution gains direction. We derive the survival-alignment tradeoff curve S = S₀·exp(−αD), prove Lyapunov stability of Mission erosion dynamics under dual-variable feedback control, present 7-dimensional phase diagrams for operational monitoring, and demonstrate a civilization-type phase transition where accumulated institutional improvements qualitatively change the system's risk profile.
Proving that fail-closed gates create a stable equilibrium in the risk-velocity state space using Lyapunov's direct method
Enterprise AI governance systems can accumulate risk over time through compounding errors, configuration drift, and expanding autonomy. This paper models governance dynamics as a continuous-time state system with risk `r` and decision velocity `v`, and control inputs gate strength `g` and evidence quality `q`. Using Lyapunov candidate `V(r, v) = alpha*r^2 + beta*v^2`, we derive conditions on `g` and `q` such that `dV/dt < 0`, establishing asymptotic stability. The resulting stability region in `(g, q)` space provides a design specification for bounded risk accumulation.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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