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    Area of Science:

    • Biosecurity
    • Artificial Intelligence
    • Molecular Biology

    Background:

    • Large language models (LLMs) demonstrate increasing biological knowledge and reasoning.
    • Concerns exist regarding LLMs' potential to facilitate biological risks.

    Purpose of the Study:

    • To evaluate LLMs' capacity for generating laboratory protocols relevant to biological threat creation.
    • To introduce a scalable, automated method for assessing LLM performance in this domain.

    Main Methods:

    • LLMs were assessed on knowledge-based questions and protocol generation for common lab techniques.
    • An automated, systematic evaluation method was developed to overcome limitations of expert-based assessments.

    Main Results:

    • LLMs possess significant knowledge of biological sciences.
    • The automated method provides a scalable approach to evaluating LLM capabilities for biosecurity risks.

    Conclusions:

    • LLMs demonstrate proficiency in biological knowledge and protocol generation.
    • The developed automated method is crucial for evaluating AI risks in the context of biological threats.