CSBA in the News

Over the last decade, stability in the South China Sea (SCS) has progressively deteriorated because of Chinese Communist Party (CCP) actions. China’s leadership has followed a long-term, multi-pronged strategy. On the military front they have constructed a “Great Wall of Sand”1 through island building, deployed an underwater “Great Wall of Sensors;”2 and completed detailed planning and preparations to establish air defense identification zones3(ADIZ) in the SCS. Despite assurances from the highest levels of the CCP leadership, they have militarized islands in the SCS,4 deployed bombers to the Paracels5 and built up military forces in the region.6 Diplomatically, the CCP has ignored international legal rulings, continued to assert sovereignty over disputed territories,7 and sought to dissuade, protest, and prevent Freedom of Navigation Operations (FONOPS).8 On the commercial front, the CCP has encouraged its large fishing fleet to overfish within other states’ exclusive economic zones (EEZs).9 When confronted, they have often harassed local fisherman and even purposely collided with them, leading to sinking vessels.10

The recent DARPA AlphaDogfight Trials (ADT) were an impressive display of both technology and competition in support of advancing American airpower. As part of a broader DARPA technology and experimentation effort called Air Combat Evolution (ACE), in just over a year, the ADT has pushed the state-of-the-art for the use of agent-based modeling and artificial intelligence () applications to air warfare. Much of the initial reporting and commentary about ADT focused on the unambiguous final result when AI defeated the human pilot in each of their five dogfights. Here, as in the past, when such a decisive result occurs, some herald it as the end of an era and the dawn of a new one, like the shift from cavalry to tanks. Conversely, skeptics highlight the unrealistic conditions that applied to the test, such as the fact that the ADT used “perfect” data during the scenario conditions, a fact that any experienced pilot or controller would identify as unrealistic. In the ADT, this meant that a kill was adjudicated by reaction time in close quarters, which gives a significant inherent advantage to the AI These artificialities aside, DARPA appropriately chose a technically challenging but simplified tactical problem for this cutting-edge experimentation in air warfare. What then should we learn from the experiment?