Are biological self-organising systems more `intelligent' than artificial intelligence (AI)? If so, why? I explore this through a mathematical lens which frames intelligence in terms of adaptability. I model systems as stacks of abstraction layers (\emph{Stack Theory}) and compare them by how they delegate agentic control down their stacks, illustrating with examples of computational, biological, human military, governmental and economic systems. Contemporary AI rests on a static, human-engineered stack in which lower layers are static during deployment. Put provocatively, static stacks resemble inflexible bureaucracies, adapting only top-down. Biological stacks are more `intelligent' because they delegate adaptation. Formally, I prove a theorem (\emph{The Law of the Stack}) showing adaptability in higher layers requires sufficient adaptability in lower layers. Generalising bio-electric explanations of cancer as isolation from collective informational structures, I explore how cancer-like failures occur in non-biological systems when delegation is inadequate. This helps explain how to build more robust systems, by delegating control like the military doctrine of mission command. It also provides a design perspective on hybrid agents (e.g. organoids, systems involving both humans and AI): hybrid creation is a boundary-condition design problem in which human-imposed constraints prune low-level policy spaces to yield desired collective behaviour while preserving collective identity.

翻译：生物自组织系统是否比人工智能（AI）更“智能”？如果是，原因何在？本文通过数学视角探讨此问题，将智能定义为适应性。我将系统建模为抽象层堆栈（\emph{堆栈理论}），并通过它们如何将主体控制权委托至下层堆栈进行比较，辅以计算系统、生物系统、人类军事系统、政府系统及经济系统的实例说明。当代AI建立在静态、人工设计的堆栈之上，其底层在部署期间保持固定。挑衅地说，静态堆栈类似于僵化的官僚体系，仅能自上而下适应。生物堆栈之所以更“智能”，是因为它们将适应性委托至下层。形式上，我证明了一个定理（\emph{堆栈定律}），表明高层适应性需要底层具备足够的适应性。通过将癌症的生物电解释推广为与集体信息结构的隔离，我探讨了当委托不足时，类癌故障如何在非生物系统中发生。这有助于解释如何通过类似军事任务指挥原则的委托控制来构建更鲁棒的系统。同时，它为混合智能体（如类器官、人机协同系统）提供了设计视角：混合创建是一个边界条件设计问题，其中人为施加的约束通过修剪低层策略空间来产生期望的集体行为，同时保持集体身份。