Receiver-Oriented Cheap Talk Design

2024-01-08

arXiv.org

AI Summary

This paper investigates how strategic information obfuscation by the sender affects equilibrium utilities in cheap-talk games when the sender’s private information precision is unknown: can the sender simultaneously improve both the receiver’s and their own equilibrium utility by selectively concealing information? We propose a receiver-centric analytical framework, introducing two novel models—“transparency-motivated communication” and “information filtering”—to mitigate the sender’s informational advantage. We theoretically establish that information filtering strictly improves the receiver’s equilibrium utility under general conditions. For the transparency-motivated setting, we provide a complete geometric characterization of the optimal equilibrium. Furthermore, we design an efficient algorithm to compute the optimal equilibrium. Our results yield computationally tractable information-design principles for user-centric platforms—such as e-commerce and social recommendation systems—where users act as receivers and require robust, incentive-aligned information structures.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Learning to Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Security and Privacy: Data transparency and provenance

Abstract

This paper considers the dynamics of cheap talk interactions between a sender and receiver, departing from conventional models by focusing on the receiver's perspective. We study two models, one with transparent motives and another one in which the receiver can emph{filter} the information that is accessible by the sender. We give a geometric characterization of the best receiver equilibrium under transparent motives and prove that the receiver does not benefit from filtering information in this case. However, in general, we show that the receiver can strictly benefit from filtering and provide efficient algorithms for computing optimal equilibria. This innovative analysis aligns with user-based platforms where receivers (users) control information accessible to senders (sellers). Our findings provide insights into communication dynamics, leveling the sender's inherent advantage, and offering strategic interaction predictions.

Problem

• Optimizes information disclosure in cheap talk games
• Explores when less information benefits both sender and receiver
• Develops algorithms for optimal information in multi-sender scenarios

Innovation

• Garbling sender information improves equilibrium utilities
• Efficient algorithms optimize binary-action information design
• Extends results to multiple-sender scenarios