Considerations on the Impact of Emerging and Disruptive Technologies on Security Policies

The issue of the impact of emerging and disruptive technologies on security policy is a major concern of the North Atlantic Treaty Alliance. This is also demonstrated by the meeting between the Board members and the newly-established Advisory Group for Emerging and Disruptive Technologies, consisting of top experts in the fields of Cyber, Artificial Intelligence, Quantum Computing, Big Data, Space, Robotics and Autonomous or Biotechnological Systems, to find new synergies between NATO, the private, governmental and academic sectors and to maintain the technological supremacy of the Alliance. At the same time, the fact that the Romanian Army has mastered the defining elements of the impact of emerging and disrupted technologies on security policy and acts to make them operational is demonstrated by the meeting of July 12, 2021, of the Minister of National Defense, Nicolae-Ionel Ciuca with Heidi Grant, director of the US Defense and Security Cooperation Agency, on which occasion Romania received from the US the name of “Dependable Undertaking (DU)” under which contracts for the purchase of military equipment can be concluded without any payment in advance. Based on these elements, we would like to continue to talk about some aspects of innovation in dual military technologies, such as the influence of emerging and disruptive technologies on the organization and use of the armed forces. The research method undertaken consisted in identifying bibliographic resources, studying them, drawing relevant conclusions and formulating points of view on the impact of emerging and disruptive technologies on security policies.

The Dark Side of Modularity: How Decomposing Problems can Increase System Complexity

Decomposition is a dominant design strategy because it enables complex problems to be broken up into loosely-coupled modules that are easier to manage and can be designed in parallel. However, contrary to widely held expectations, we show that complexity can increase substantially when natural system modules are fully decoupled from one another to support parallel design. Drawing on detailed empirical evidence from a NASA space robotics field experiment we explain how new information is introduced into the design space through three complexity addition mechanisms of the decomposition process: interface creation, functional allocation, and second order effects. These findings have important implications for how modules are selected early in the design process and how future decomposition approaches should be developed. Although it is well known that complex systems are rarely fully decomposable and that the decoupling process necessitates additional design work, the literature is predominantly focused on reordering, clustering, and/or grouping based approaches to define module boundaries within a fixed system representation. Consequently, these approaches are unable to account for the (often significant) new information that is added to the design space through the decomposition process. We contend that the observed mechanisms of complexity growth need to be better accounted for during the module selection process in order to avoid unexpected downstream costs. With this work we lay a foundation for valuing these complexity-induced impacts to performance, schedule and cost, earlier in the decomposition process.

When Decomposition Increases Complexity: How Decomposing Introduces New Information Into the Problem Space

Decomposition is a dominant design strategy because it enables complex problems to be broken up into more manageable modules. However, although it is well known that complex systems are rarely fully decomposable, much of the decomposition literature is framed around reordering or clustering processes that optimize an objective function to yield a module assignment. As illustrated in this study, these approaches overlook the fact that decoupling partially decomposeable modules can require significant additional design work, with associated consequences that introduce considerable information to the design space. This paper draws on detailed empirical evidence from a NASA space robotics field experiment to elaborate mechanisms through which the processes of decomposing can add information and associated descriptive complexity to the problem space. Contrary to widely held expectations, we show that complexity can increase substantially when natural system modules are fully decoupled from one another to support parallel design. We explain this phenomenon through two mechanisms: interface creation and functional allocation. These findings have implications for the ongoing discussion of optimal module identification as part of the decomposition process. We contend that the sometimes-significant costs of later stages of design decomposition are not adequately considered in existing methods. With this work we lay a foundation for valuing these performance, schedule and complexity costs earlier in the decomposition process.