Trias Algorithmica: What Code Rules - Hamilton Mann

Understand how algorithmic power governs society and how to hold it accountable While much of the public debate remains focused on whether AI systems are truly intelligent, when they may surpass human intelligence, or how useful or dangerous they may become, the deeper issue is being overlooked. Today's most powerful algorithmic systems increasingly reassemble powers that political thought once deliberately separated under the doctrine of Trias Politica. The book argues that compute, energy, training operate as an algorithmic executive; that code, model design, optimization targets, and embedded constraints function as an algorithmic legislature; and that evaluation, auditing, and benchmarking function as an algorithmic judiciary. What would be intolerable for many, the fusion of rulemaking, execution, and judgment, is becoming the standard of our society enabled by algorithmic systems. They now shape access, opportunity, and justice at machine speed - yet they operate largely beyond democratic scrutiny. Trias Algorithmica: What Code Rules, by Hamilton Mann, a Thinkers50 honouree, originator of the concept of Artificial Integrity, and leading authority in AI transformation, traces where this power originates, how it sustains itself through manufactured dependence, and what a constitutional framework for algorithmic governance must look like. The book introduces original concepts including aggregogenous monopoly, Technological Stockholm Syndrome, dependautonomy, and unpacks the revaluing mechanism of work. It also presents a practical framework of nine critical questions for interrogating algorithmic power deployment. It proposes algorithmic safety cases as constitutional safeguards alongside eight principles for separating design, oversight, and enforcement functions as a new Trias Politica for the age of code - preventing concentrated, self-judging systems from operating unchecked at scale across organisations and public institutions. You'll also explore: How concentrated AI infrastructures turn code into enforceable law and corporate product into policy revealing how trust becomes the social license for algorithmic power. The spectrum of human-in-the-loop roles, from genuine oversight to compliance instruments effectively displaced by automation Why algorithmic efficiency gains can expand harmful uses unless constrained by deliberate macro-level governance boundaries How data-driven valuation systems reshape human worth through taskification, rankings, a