Your browser doesn't support javascript.
loading
Can Generative AI improve social science?
Bail, Christopher A.
Afiliación
  • Bail CA; Department of Sociology, Duke University, Durham, NC 27708.
Proc Natl Acad Sci U S A ; 121(21): e2314021121, 2024 May 21.
Article en En | MEDLINE | ID: mdl-38722813
ABSTRACT
Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the potential to improve survey research, online experiments, automated content analyses, agent-based models, and other techniques commonly used to study human behavior. In the second section of this article, I discuss the many limitations of Generative. I examine how bias in the data used to train these tools can negatively impact social science research-as well as a range of other challenges related to ethics, replication, environmental impact, and the proliferation of low-quality research. I conclude by arguing that social scientists can address many of these limitations by creating open-source infrastructure for research on human behavior. Such infrastructure is not only necessary to ensure broad access to high-quality research tools, I argue, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ciencias Sociales / Inteligencia Artificial Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ciencias Sociales / Inteligencia Artificial Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article