Benjamin Jensen and Yasir Atalan
Artificial intelligence (AI) is the new arms race and the centerpiece of defense modernization efforts across multiple countries, including the United States. Yet, despite the surge in AI investments, both Silicon Valley and the Pentagon struggle to answer one simple question: How can decisionmakers know if AI actually works in the real world?
The standard approach to answer this question is an evaluation practice called benchmarking. Benchmarking is defined as “a particular combination of a dataset or sets of datasets . . . and a metric, conceptualized as representing one or more specific tasks or sets of abilities, picked up by a community of researchers as a shared framework for the comparison of method.” This practice allows the researchers to evaluate and compare AI model performance, for example, how well a large language model (LLM) answers questions about military planning. Yet, proper benchmarking studies are few and far between for national security.
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