On the Inefficiency of Social Learning

2026-02-09

AI Summary

This study addresses the inefficiencies in social learning arising from information externalities in sequential decision-making environments. It investigates whether a social planner can restore efficient learning by jointly designing an information disclosure mechanism and behavior-based monetary transfers under a finite budget constraint. Integrating tools from game theory, information economics, and mechanism design, the paper demonstrates that even when both the information structure and incentive scheme are optimally coordinated, inefficient social learning cannot be fully corrected if the total expected monetary transfers are bounded by a limited budget. This result establishes a fundamental limitation on achieving socially efficient learning through constrained interventions and delineates a theoretical boundary for the design of policy instruments aimed at mitigating inefficiencies in decentralized learning processes.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition

Application Category

• Economics, Online Markets and Human Computation: Social networks and social learning
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks

Abstract

We study whether a social planner can improve the efficiency of learning, measured by the expected total welfare loss, in a sequential decision-making environment. Agents arrive in order and each makes a binary action based on their private signal and the social information they observe. The planner can intervene by jointly designing the social information disclosed to agents and offering monetary transfers contingent on agents'actions. We show that, despite such flexibility, efficient learning cannot be restored with a finite budget: whenever learning is inefficient without intervention, no combination of information disclosure and transfers can achieve efficient learning while keeping total expected transfers finite.

Problem

• social learning
• efficiency
• sequential decision-making
• information disclosure
• monetary transfers

Innovation

• social learning
• information design
• monetary transfers
• efficiency
• sequential decision-making