New framework evaluates LLMs as surrogate experts in security surveys

A new framework has been developed to evaluate the reliability and biases of using Large Language Models (LLMs) as surrogate experts in security research surveys. The study found that while LLMs can generate internally consistent answers, they tend to exhibit reduced variance and homogenized opinions compared to human experts. The research suggests LLMs are valuable for initial exploration and hypothesis generation but should not replace direct expert elicitation in security operations centers. AI

IMPACT Provides methodological guidance for researchers using LLMs in surveys, highlighting limitations and appropriate use cases.

RANK_REASON The cluster contains a research paper detailing a new methodology. [lever_c_demoted from research: ic=1 ai=1.0]

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