Speaker:  Laurie A. Schintler, associate professor in the Schar School of Policy and Government at George Mason University, and director of data and technology research initiatives in the Center for Regional Analysis.

Abstract: Recent advancements in artificial intelligence (AI) systems, including large language models like ChatGPT, offer promise and peril for scholarly peer review. On the one hand, AI can enhance efficiency by addressing issues like long publication delays. On the other hand, it brings ethical and social concerns that could compromise the integrity of the peer review process and outcomes. However, human peer review systems are also fraught with related problems, such as biases, abuses, and a lack of transparency, which already diminish credibility. While there is increasing attention to the use of AI in peer review, discussions revolve mainly around plagiarism and authorship in academic journal publishing, ignoring the broader epistemic, social, cultural, and epistemic positionality of peer review. In this talk, I will provide an overview of the current NSF-funded project, a collaboration between the Schar School and the Department of Sociology and Anthropology at George Mason University, to assess the ethics and legitimacy of AI for peer review by gauging researchers’ perceptions about algorithmic versus human-mediated peer review. I will discuss how the project and collaboration transpired and our broader research agenda in this area. Moreover, I will delineate ideas and plans for future research and proposals with the hope of engaging CAHMP members in these endeavors or stimulate even more ideas.