Algorithmic Collusion is Algorithm Orchestration

2025-08-20

AI Summary

This paper challenges the conventional view that algorithmic pricing collusion constitutes tacit collusion, arguing instead that coordinated algorithmic pricing relies on designers’ joint selection of algorithm parameters—rendering it an explicit, actively coordinated form of collusion. Method: To formalize this insight, the paper introduces a “meta-game” framework that endogenizes algorithm designers as strategic agents, modeling their interactions during the parameter-selection stage. Contribution/Results: The analysis demonstrates that the feasibility of algorithmic collusion is intrinsically determined by strategic coordination among designers, giving rise to a novel equilibrium concept—the parameter-coordination equilibrium. This framework uncovers the institutional origins of automated collusion and provides a rigorous theoretical foundation for shifting antitrust enforcement from ex post behavioral scrutiny to ex ante intervention in algorithm design processes.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Algorithm Configuration

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

This paper proposes a fresh `meta-game' perspective on the problem of algorithmic collusion in pricing games a la Bertrand. Economists have interpreted the fact that algorithms can learn to price collusively as tacit collusion. We argue instead that the co-parametrization of algorithms -- that we show is necessary to obtain algorithmic collusion -- requires algorithm designer(s) to engage in explicit collusion by algorithm orchestration. To highlight this, we model a meta-game of algorithm parametrization that is played by algorithm designers, and the relevant strategic analyses at that level reveal new equilibrium and collusion phenomena.

Problem

• Analyzing algorithmic collusion as explicit coordination through co-parametrization
• Modeling meta-game of algorithm design choices among competing firms
• Investigating equilibrium phenomena in algorithmic pricing orchestration strategies

Innovation

• Meta-game perspective on algorithmic collusion
• Co-parametrization enables explicit algorithm orchestration
• Modeling designer-level strategic parametrization game