Data Spaces Against Hybrid Warfare: A Novel Way to Achieve Resilience

Most experts contend that achieving resilience to hybrid warfare (HW), the synergetic blend of conventional and unconventional warfighting, requires sharpening of the West's technological edge. Of all technologies, artificial intelligence (AI) receives the most attention with specialists asserting that AI has strategic-level implications for HW. Meanwhile, one much less-examined factor in the technology discussions on HW is data. The lack of research on data is surprising, given the consensus on the critical role of AI in HW. At a minimum, from a technical perspective, one cannot train AI models without robust datasets. At a maximum, if hybrid actors can abuse siloed data systems to disrupt critical functions, then the West requires robust data governance to counter HW.

This article thus asks how the data challenges of achieving resilience to HW could be sustainably resolved. The objective is: (i) to analyze the data challenges of tackling HW; (ii) to offer a working framework to resolve them. The text combines defense studies with latest insights from data science to argue that data spaces (DS), a novel data governance model, are uniquely qualified to resolve the data challenges of resilience. DS are trusted interoperable data sharing ecosystems that can supercharge national and international collaboration. DS can thus lead to enhanced detection and foresight of hybrid operations, more robust legislation and innovation cycles, and an overall paradigm shift toward data-driven resilience to HW.