Abstract
AbstractThe introduction contextualizes and summarizes the key results of the 25 case studies along the six lines of effort that constitute the analytical framework of the country analyses. First, it argues that core strategic motives, the role of partners and challengers, and a human or tech-centric understanding of defense AI shape the respective national approaches. Taken together the prevailing perspectives lead to a collective “lock-in” as all countries analyzed operate in a human and data-centric paradigm. Second, this affects current defense AI development priorities. Most nations develop AI in tandem with uncrewed systems, for example, for intelligence, reconnaissance, and surveillance missions, to support predictive maintenance and logistics, advance command and control, and further data analytics and data management. Third, in view of preparing for the use of defense AI many countries have set up new cross-functional entities to advance defense AI or improve AI-related technology developments. Most countries, however, have entrusted existing organizational entities with these tasks. In addition to organizational change at the ministerial level, some countries also introduce novel elements at service and command levels. Fourth, funding for defense AI is most difficult to compare as an internationally accepted spending taxonomy on defense AI is missing. Some nations operate in opaqueness as they do not publicly disclose financial figures. Others have dedicated AI budget lines, fund defense AI as part of ongoing procurement projects, and one country has ensured interagency funding. Fifth, in line with the development priorities, most nations also field defense AI for the use with uncrewed assets, followed by target identification/detection and data analytics. Almost every second country uses defense AI for predictive maintenance, logistics and simulation-based training. Most importantly, “learning by procuring” is an important inroad for defense AI to enter a foreign market via the defense solution procured from a partner. Finally, training for defense AI is evolving slowly. About a third of the countries focus on training only for the military service workforce. The same number of countries is also active in training civilian defense and military service workforces. Fewer countries also look at training the defense industrial workforce. Some countries also launch dedicated data training initiatives.
Publisher
Springer Nature Switzerland
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