Abstract
How do Lethal Autonomous Weapons Systems (LAWS) shape escalation dynamics between India and China in a chaoplexic, AI-driven battlespace? While existing research – from Scharre on autonomy to Sweijs and Zilincik on cross-domain deterrence, and from Winter, Galliott, Colijn, Podar, and Hanley on legality, ethics, risk, and Chinese escalation behavior provides valuable insights, these perspectives remain largely siloed. What is insufficiently explored is how technological, legal, ethical, and doctrinal factors interact when autonomy compresses decision cycles and obscures intent. To address this gap, the study analyzes a self-developed Scenario Building Exercise and employs two game-theory models – the Prisoner’s Dilemma and Backward Induction Theory, to trace how unintended outcomes may arise. Using the Institutional Analysis and Development (IAD) Framework, it evaluates contextual variables, actor positions, and interaction patterns as sources of cumulative instability. The study argues that LAWS lower risk thresholds, heighten opacity, and accelerate decision-making, thereby pushing strategic behavior toward escalation. By so examining LAWS in structural terms, this study addresses a key conceptual gap with findings that may help develop an autonomous-era escalation continuum for the Sino-Indian context.
