AI for War and Peace examines the rapidly evolving relationship between artificial intelligence and armed conflict, and its implications for diplomacy and peacebuilding. AI-assisted intelligence and target identification have shaped military campaigns in Gaza and Iran, while AI-enhanced drone systems deployed in Ukraine are enabling autonomous functions and reshaping asymmetric conflict. These developments are embedded in the broader geopolitical contest for AI primacy — including resource-based competition for energy, critical minerals, and the infrastructure underpinning AI systems — alongside the growing role of AI-enhanced cyber operations and information warfare as persistent features of contemporary conflict. As AI accelerates military deliberations, this efficiency risks reducing the window for de-escalation and preventive diplomacy. This book analyzes what these shifts demand of diplomats and peacebuilders — charting new territory across AI-driven geopolitical competition, new resource-based contests, military AI governance, and persistent cyber conflict.

Outcomes of civil wars differ greatly across countries, even among states with comparable conflict risks — poverty, ethnic cleavages, political instability, and state weakness. Understanding why some civil conflicts terminate through peace agreements or military victories while others fail to end decisively requires attention to the strategic interactions between rebels and states, and how rebel groups mutate and shape competition to reach different conflict outcomes. Yet the critical link between rebel group characteristics — their pre-war organizations, internal dynamics, alliances, and coercive capacities — and conflict outcomes remains under-theorized and empirically underdeveloped.

This book addresses that gap by examining how rebel groups influence civil war outcomes. Drawing on mixed methods — including quantitative analysis of 346 civil conflict outcomes from 1946–2012 and case studies of four conflicts in South and Southeast Asia (Bangladesh, Indonesia, Sri Lanka, and Myanmar) — it demonstrates how rebel features and the number of armed groups shape prospects for victory, defeat, political settlement, or non-decisive outcome. Conflict outcome models incorporating new rebel-group variables predict war outcomes with 83.6 percent accuracy. The study makes two core contributions: first, it integrates non-decisive conflict outcomes into a civil war bargaining framework, demonstrating how rebel organizational changes shape these scenarios; second, it builds new theoretical and empirical links between rebel group lifecycles, the bargaining process, and civil war outcomes. The findings carry strategic implications for states and rebel groups engaged in conflict and for third parties seeking to resolve it.

Dissertation to book project:

Doctoral Dissertation, The Australian National University, May 2024. http://hdl.handle.net/1885/317367

Non-decisive conflict outcomes—instances in which violence ends without a clear victory or formal settlement—are frequent yet understudied scenarios in civil wars. Existing war termination scholarship and rationalist bargaining approaches typically rely on a "win, lose, or draw" framework that fails to capture how conflicts end without clear symbols of termination. This omission limits theoretical understanding of the bargaining processes that produce non-decisive outcomes and narrows the perceived range of rational options available to conflict actors seeking an off-ramp when neither victory nor a negotiated settlement is attainable. This article addresses these theoretical and empirical gaps through three contributions. First, it refines rationalist bargaining approaches by identifying commitment challenges that explain why conflict actors rationally avoid both fighting and sincere negotiations, sustaining non-decisive equilibria such as mutually beneficial stalemates. Second, it develops a typology conceptualizing three distinct categories of non-decisive conflict outcomes—Territorial Change, Rebel Reboot, and Conflict Management—advancing explanations for previously overlooked empirical cases. Third, it illustrates variation across non-decisive outcomes through an empirical analysis of Myanmar's armed conflicts. The findings demonstrate that non-decisive outcomes function as strategic pathways shaped by rational choices, helping scholars and policymakers more effectively recognize and study these alternative endpoints.

Multi-actor conflicts have become the dominant form of civil war, affecting 65 percent of conflict countries during 2015-2024. I examine how rebel proliferation affects outcomes by analyzing intrastate conflicts from 1946-2012 using random-effects multinomial logit models. Multi-actor dynamics reduce military victories and peace agreements while producing conflict-management outcomes involving reduced violence and limited cooperation. Rebel splintering constrains government victory (89%), whereas concurrent original rebels reduce both government (76%) and rebel victories (90%). When settlements occur in fragmented conflicts, 83 percent are partial agreements excluding groups, highlighting sequential peacemaking pathways. These findings support my theoretical argument: conflict parties strategically pursue non-decisive outcomes sustained by mutually beneficial stalemates—equilibria in which maintaining the status quo yields higher returns than renewed fighting for uncertain military gains or comprehensive settlements that risk commitment failures. In multi-actor settings, rebels and states pursue organizational survival, with states avoiding overextension and rebels limiting violence through conflict-management scenarios.

Nearly half of all intrastate conflicts between 1946 and 2023 ended without military victory or formal peace agreement, yet civil war scholarship lacks a satisfactory mechanism to explain how these non-decisive outcomes emerge and endure. Existing "win, lose, or draw" rationalist bargaining frameworks treat settlements as the default outcome when neither party prevails militarily—a logic that assumes impasse reliably produces the ripe moment Zartman describes. As conflict systems grow more complex, however, negotiated settlements have continued to decline. This theory note introduces mutually beneficial stalemates—an equilibrium in which conflict parties calculate that maintaining the status quo yields higher returns than renewed fighting or settlements that risk commitment failures—as a mechanism to explain how non-decisive outcomes evolve and are sustained, sometimes outlasting average peace agreement duration. Where Zartman's mutually hurting stalemate describes a painful impasse generating pressure toward settlement, the mutually beneficial stalemate explains transitions to conflict-management outcomes characterized by limited violence and selective cooperation. I develop a logic of joint conflict avoidance to show how parties protect existing gains and preserve organizations against risks posed by both escalation and resolution. I extend the framework to multi-actor conflicts, where rebel proliferation and external intervention structurally reinforce non-decisive equilibria.