How does uncertainty over a critical asset with the potential to change future balance of power affect conflict and communication patterns in multilateral bargaining? Open Access

Abstract

Artificial intelligence (AI) has emerged as a transformative technology with significant implications for both economic development and military power. As a result, control over its hardware, particularly the semiconductor and chip industry in Taiwan, has become a central geopolitical concern within the China-Taiwan-U.S. triangular relationship. However, the future of AI technology remains uncertain, which may stem from either imperfect information regarding its prospects or incomplete information that Taiwan possesses regarding its potential. Furthermore, if AI is deemed critical in altering the future balance of power between the United States and China, the U.S. is likely to intervene preemptively when China employs force against Taiwan. Drawing upon Fearon’s (1995) rationalist framework for interstate conflict—specifically the commitment problem and private information—this study employs formal modeling to analyze how uncertainty surrounding a vital asset with the potential to shift the future balance of power can reshape crisis bargaining among three major powers. In scenarios where information concerning the asset's prospects is imperfect, a third party may be encouraged to disclose their type truthfully in private to its ally, even when incentivized to freeride on an ally’s wartime efforts. Additionally, the asset's prospects positively correlate with the likelihood of multilateral war. However, when the asset is too imperative in altering the future balance of power, the rising power is likely to consistently avoid actions that risk war. When such information is exclusive to the target state, it will refrain from sending cooperative signals to the third party and will reject any low offers, aiming to entangle the third party in a multilateral war. In this scenario, the likelihood of war increases and may proliferate when prior beliefs indicate that the asset is substantial.

Table of Contents

Introduction

Past Models on Commitment Problem, Private Information, and Crisis Bargaining

Case Study: The Prospect of AI technology and the Taiwan dilemma

Baseline Model

Extension Model

Key Features

Analysis of Baseline

Analysis of Extension

Implication

Conclusion

Reference

Multimedia Reference

Appendix

About this Honors Thesis

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School	Emory College
Department	Political Science and Mathematics
Degree	B.A.
Submission	Honors Thesis
Language	English
Research Field	Political Science, International Relations
Keyword	Third Party Formal Modeling Interstate Conflict Crisis Bargaining
Committee Chair / Thesis Advisor	Sun, Jessica, Emory University
Committee Members	Sexton, Renard, Emory University Wang, Yiran, Emory University Reiter, Dan, Emory University

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