Some politicians and pundits believe that, in the AI era, the military with the most data wins. A new analysis disputes this notion.

What’s new: A report by Georgetown University’s Center for Security and Emerging Technology examines the relative strengths of the Chinese and U.S. militaries in AI.

What it says: Data points come in many forms and degrees of usefulness, the authors note. Thus, the size of a country’s data trove doesn’t translate directly into power. A more important factor is the degree to which a country can use data to gain an edge in developing military systems.

  • Unlike the U.S. government, China has the power to requisition vast troves of commercial data for military use. But commercial data is often useless for military AI applications. A self-driving tank trying to navigate a shell-pocked landscape would get no help from traffic data gathered by self-driving cars used by civilians, for instance.
  • Instead, data management is key: gathering, cleaning, labeling, storing, and optimizing data so it suits the job at hand. Good data management accelerates the process of bringing prototypes to deployment.
  • Moreover, emerging techniques like few-shot learning and synthetic data could make stockpiling huge datasets less important.
  • The report concludes that no country currently has a clear advantage in military AI. Rather, different countries have distinct strengths and weaknesses.

Behind the news: The Chinese government began to emphasize big data in 2014 and since has launched efforts to industrialize data collection across all sectors of its economy and military. Its U.S. counterpart began working on its AI strategy last year and still hasn’t fully organized its cloud computing infrastructure.

Why it matters: More nuanced thinking about the relative value of various datasets can help military planners focus on what really matters without worrying over who has the biggest pile of petabytes.

We’re thinking: Datasets are often verticalized, and data from one domain often aren’t directly useful in another. Oversimplifications of the value of data don’t help us find the right data to make our systems work. In any case, every nation has a stake in avoiding the weaponization of AI.

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