生成语法
计算机科学
人工智能
社会模拟
心理学
数据科学
作者
Thomas Davidson,Daniel Karell
标识
DOI:10.1177/00491241251339184
摘要
Generative artificial intelligence (AI) offers new capabilities for analyzing data, creating synthetic media, and simulating realistic social interactions. This essay introduces a special issue that examines how these and other affordances of generative AI can advance social science research. We discuss three core themes that appear across the contributed articles: rigorous measurement and validation of AI-generated outputs, optimizing model performance and reproducibility via prompting, and novel uses of AI for the simulation of attitudes and behaviors. We highlight how generative AI enable new methodological innovations that complement and augment existing approaches. This essay and the special issue’s ten articles collectively provide a detailed roadmap for integrating generative AI into social science research in theoretically informed and methodologically rigorous ways. We conclude by reflecting on the implications of the ongoing advances in AI.
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