Alignment as Institutional Design: From Behavioral Correction to Transaction Structure in Intelligent Systems

TL;DR

This paper proposes viewing AI alignment as an institutional design problem, emphasizing transaction structures and economic principles to create robust, self-correcting systems rather than relying solely on behavioral correction methods.

Contribution

It introduces a novel framework that transforms AI alignment into a political-economy problem using institutional design principles inspired by economics.

Findings

Alignment can be achieved through transaction structures that make misalignment costly and detectable.

Three levels of human intervention are identified: structural, parametric, and monitorial.

The framework promotes institutional robustness over perfection in alignment strategies.

Abstract

Current AI alignment paradigms rely on behavioral correction: external supervisors (e.g., RLHF) observe outputs, judge against preferences, and adjust parameters. This paper argues that behavioral correction is structurally analogous to an economy without property rights, where order requires perpetual policing and does not scale. Drawing on institutional economics (Coase, Alchian, Cheung), capability mutual exclusivity, and competitive cost discovery, we propose alignment as institutional design: the designer specifies internal transaction structures (module boundaries, competition topologies, cost-feedback loops) such that aligned behavior emerges as the lowest-cost strategy for each component. We identify three irreducible levels of human intervention (structural, parametric, monitorial) and show that this framework transforms alignment from a behavioral control problem into a political-economy problem. No institution eliminates self-interest or guarantees optimality; the best design makes misalignment costly, detectable, and correctable. We conclude that the proper goal is institutional robustness-a dynamic, self-correcting process under human oversight, not perfection. This work provides the normative foundation for the Wuxing resource-competition mechanisms in companion papers. Keywords: AI alignment, institutional design, transaction costs, property rights, resource competition, behavioral correction, RLHF, cost truthfulness, modular architecture, correctable alignment