Unmanned Aerial Vehicles: Do They Pose Legal Challenges?

Abstract

While Unmanned Aerial Vehicles (UAVs) have been part of warfare for over 150 years, the recent increase in their use, particularly as part of targeted strikes in Afghanistan, Pakistan and Yemen, has resulted in heightened public and academic interest. A significant amount of the public and academic debate has focused on public international law issues. This chapter examines the most relevant aspects of international law to UAV operations, namely the law concerning the resort to and use of force by states (jus ad bellum and jus in bello). Drawing on the recently released Manual on International Law Applicable to Air and Missile Warfare published by the Program on Humanitarian Policy and Conflict Research at Harvard University, the authors critically examine the following main legal issues in relation to UAV operations: can a state respond in national self-defence to the actions of a non-state actor acting independently of any state; can a state use force in the territory of a third state against a non-state actor (what are the geographic limits of a non-international armed conflict?); what is the status of a civilian operator of a UAV in a non-international armed conflict; and is there is an obligation under the law of armed conflict to positively consider the option of capture prior to attempting to kill? While the authors believe that there are preferred legal positions to be adopted on these points, it would be misleading to indicate that there are concluded positions that represent ‘the law’. Rather, there is a variety of views, some of which command more or less agreement from states, judicial fora and commentators. Some positions certainly are more consistent with historical and more recent state practice, and it is generally those positions that the authors have found more persuasive.KeywordsArmed ConflictTrial ChamberGeneva ConventionHumanitarian PolicyArmed AttackThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.