(Re)Doing Science with Artificial Intelligence
(Re)Doing Science with Artificial Intelligence
Abstract Submissions Closed
RC23 Sociology of Science and Technology (host committee)
Language: English
Session Type: Oral
Artificial Intelligence (AI) is fundamentally reshaping the production, validation, and dissemination of scientific knowledge. From automated data analysis and predictive modeling to autonomous laboratory discoveries, AI technologies are altering not only scientific practices but also the institutional, ethical, and epistemological foundations of knowledge production itself.
This section invites contributions that sociologically examine the integration of AI across diverse scientific domains. We welcome papers from multiple sociological subfields, including the sociology of science and technology, sociology of knowledge, organizational sociology, and digital sociology, to critically explore these rapid transformations.We welcome diverse theoretical perspectives and methodological approaches—qualitative, quantitative, or mixed methods—that offer fresh, critical insights into how AI is redefining what it means to do science in the 21st century.
We encourage submissions addressing the profound epistemological shifts in how AI alters concepts of objectivity and proof, as well as changes to academic labor, human-machine collaboration, and the research division of labor. Additionally, we seek analyses of the institutional and power dynamics influencing funding, publishing, and geopolitical inequalities in global science, alongside investigations into the ethics, governance, and commercialization of scientific AI tools. Finally, papers may explore how AI impacts science communication, public trust in expertise, and policy-making.
This section invites contributions that sociologically examine the integration of AI across diverse scientific domains. We welcome papers from multiple sociological subfields, including the sociology of science and technology, sociology of knowledge, organizational sociology, and digital sociology, to critically explore these rapid transformations.We welcome diverse theoretical perspectives and methodological approaches—qualitative, quantitative, or mixed methods—that offer fresh, critical insights into how AI is redefining what it means to do science in the 21st century.
We encourage submissions addressing the profound epistemological shifts in how AI alters concepts of objectivity and proof, as well as changes to academic labor, human-machine collaboration, and the research division of labor. Additionally, we seek analyses of the institutional and power dynamics influencing funding, publishing, and geopolitical inequalities in global science, alongside investigations into the ethics, governance, and commercialization of scientific AI tools. Finally, papers may explore how AI impacts science communication, public trust in expertise, and policy-making.
Session Organizers: