AI’s Missing Separation Of Powers

We have spent much of the AI governance debate asking what artificial intelligence should be allowed to do. I believe there is a prior question we have not examined closely enough: what makes algorithmic power legitimate?

Montesquieu’s warning about concentrated power was written for political institutions, not algorithms. Yet the principle behind it has surprising relevance to AI. When the same organization can effectively design an algorithmic system, authorize its deployment and determine whether its consequences are acceptable, three forms of power that democratic institutions deliberately separate can collapse into one.

That is the premise I explore in my new book, Trias Algorithmica: What Code Rules, and it was the starting point for a recent conversation with Matt Symonds, Chief Editor of BlueSky Thinking, a platform covering business education and management research.

Our conversation moved from the distinction between legality and legitimacy to what independent approval mechanisms for AI could look like before systems reach the public—and ultimately to one practical question I believe every board and executive team should be able to answer: Who can stop whom?

What follows is an edited version of my conversation with Matt, originally published by BlueSky Thinking.

Matt Symonds: Your first book, Artificial Integrity asked whether machines can be built to hold a moral compass. Trias Algorithmica asks who gave them authority in the first place. What changed between the two books?

Hamilton Mann: Artificial Integrity began with the machine. Trias Algorithmica begins with power. So what has changed is the unit of analysis.

Trias Algorithmica goes one level up. Even if we could build a machine that puts integrity above intelligence, should that machine, and the organisation behind it, be authorised to exercise power over other people in the first place? The question is no longer only the quality of algorithmic judgment. It is the legitimacy of algorithmic power.