Alignment as Institutional Design: From Behavioral Correction to Transaction Structure in Intelligent Systems
For AI safety researchers, this work reframes alignment from a behavioral control problem to a political-economy problem, offering a new conceptual foundation.
The paper argues that current AI alignment methods (e.g., RLHF) are analogous to an economy without property rights and do not scale, proposing instead an institutional design framework where aligned behavior emerges from internal transaction structures. It identifies three levels of human intervention and concludes that the goal should be institutional robustness rather than perfection.
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