“善变”的智慧:利用法学硕士作为政治和社会科学推理的工具。

IF 18.3 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Lisa P. Argyle, Ethan C. Busby, Joshua R. Gubler, Bryce Hepner, Alex Lyman, David Wingate
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引用次数: 0

摘要

为了促进大型语言模型(llm)的科学使用,我们建议政治和社会科学的研究人员重新关注推理的科学目标。我们认为,这种重新聚焦将改善关于这些工具及其在社会科学中的应用的共享科学知识的积累。我们讨论与法学硕士科学推理相关的挑战和机遇,使用模型输出的验证作为讨论的说明性案例。然后,我们提出了一套与确定法学硕士在完成特定任务时的失败和成功相关的指导方针,并讨论了如何从这些观察中做出推论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Arti-‘fickle’ intelligence: using LLMs as a tool for inference in the political and social sciences
To promote the scientific use of large language models (LLMs), we suggest that researchers in the political and social sciences refocus on the scientific goal of inference. We suggest that this refocus will improve the accumulation of shared scientific knowledge about these tools and their uses in the social sciences. We discuss the challenges and opportunities related to scientific inference with LLMs, using validation of model output as an illustrative case for discussion. We then propose a set of guidelines related to establishing the failure and success of LLMs when completing particular tasks and discuss how to make inferences from these observations. Large language models are increasingly important in social science research. The authors provide guidance on how best to validate and use these models as rigorous tools to further scientific inference.
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CiteScore
11.70
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