Daniel Trusilo investigates the concept of emergent behavior in complex autonomous systems and its implications in dynamic, open context environments such as conflict scenarios. In a nuanced exploration of the intricacies of autonomous systems, the author employs two hypothetical case studies—an intelligence, surveillance, and reconnaissance (ISR) maritime swarm system and a next-generation autonomous humanitarian notification system—to articulate and elucidate the effects of emergent behavior.
In the case of the ISR swarm system, the author underscores how the autonomous algorithm’s unpredictable micro-level behavior can yield reliable macro-level outcomes, enhancing the system’s robustness and resilience against adversarial interventions. Conversely, the humanitarian notification system emphasizes how such systems’ unpredictability can fortify International Humanitarian Law (IHL) compliance, reducing civilian harm, and increasing accountability. Thus, the author emphasizes the dichotomy of emergent behavior: it enhances system reliability and effectiveness while posing novel challenges to predictability and system certification.
Navigating these challenges, the author calls attention to the implications for system certification and ethical interoperability. With the potential for these systems to exhibit unforeseen behavior in actual operations, traditional testing, evaluation, verification, and validation methods seem inadequate. Instead, the author suggests adopting dynamic certification methods, allowing the systems to be continually monitored and adjusted in complex, real-world environments, thereby accommodating emergent behavior. Ethical interoperability, the concurrence of ethical AI principles across different organizations and nations, presents another conundrum, especially with differing ethical guidelines governing AI use in defense.
In its broader philosophical framework, the article contributes to the ongoing discourse on the ethics and morality of AI and autonomous systems, particularly within the realm of futures studies. It underscores the tension between the benefits of autonomous systems and the ethical, moral, and practical challenges they pose. The emergent behavior phenomenon can be seen as a microcosm of the larger issues in AI ethics, reflecting on themes of predictability, control, transparency, and accountability. The navigation of these ethical quandaries implies the need for shared ethical frameworks and standards that can accommodate the complex, unpredictable nature of these systems without compromising the underlying moral principles.
In terms of future research, there are several critical avenues to explore. The implications of emergent behavior in weaponized autonomous systems need careful examination, questioning acceptable risk confidence intervals for such systems’ predictability and reliability. Moreover, the impact of emergent behavior on operator trust and the ongoing issue of machine explainability warrants further exploration. Lastly, it would be pertinent to identify methods of certifying complex autonomous systems while addressing the burgeoning body of distinct, organization-specific ethical AI principles. Such endeavors would help operationalize these principles in light of emergent behavior, thereby contributing to the development of responsible, accountable, and effective AI systems.
Abstract
The development of complex autonomous systems that use artificial intelligence (AI) is changing the nature of conflict. In practice, autonomous systems will be extensively tested before being operationally deployed to ensure system behavior is reliable in expected contexts. However, the complexity of autonomous systems means that they will demonstrate emergent behavior in the open context of real-world conflict environments. This article examines the novel implications of emergent behavior of autonomous AI systems designed for conflict through two case studies. These case studies include (1) a swarm system designed for maritime intelligence, surveillance, and reconnaissance operations, and (2) a next-generation humanitarian notification system. Both case studies represent current or near-future technology in which emergent behavior is possible, demonstrating that such behavior can be both unpredictable and more reliable depending on the level at which the system is considered. This counterintuitive relationship between less predictability and more reliability results in unique challenges for system certification and adherence to the growing body of principles for responsible AI in defense, which must be considered for the real-world operationalization of AI designed for conflict environments.
Autonomous AI Systems in Conflict: Emergent Behavior and Its Impact on Predictability and Reliability