Event Details

Speaker: Brian Uzzi, Kellogg-Northwestern University
Location: Open to the public virtually, via Zoom

Friday, April 12, 2024 from 11am – 12pm

Join Zoom meeting: https://usc.zoom.us/j/95888595423?pwd=VHBLa041dUJWcWx0NEhuYmQrV29ZQT09

Zoom meeting ID: 958 8859 5423
Passcode: 318968

Hosted by: Zhuoyu Shi
POC: Karen Lake

Abstract: Innovation involves recombining past knowledge. The increasing rate at which scientific knowledge is expanding should bode well for innovation. Nevertheless, problems related to creating replicable science and appraising the merits of new ideas threaten innovation. In study 1, we use artificial intelligence to examine the replication problem in science. We estimate a paper’s replicability using ground truth, manual replication data, and then test the model’s accuracy on an extensive set of out-of-sample studies. The model’s accuracy is better than reviewer base rates and on par with prediction markets. We then conduct a discipline-wide census of replicability in psychology for the past 20 years. Replicability failures varies widely by subfield and is highest for experimental studies and papers receiving media coverage. In study 2, we investigate how the merits of innovative ideas communicated in science. Here we conduct semantic analyses of grant application success with a focus on scientific promotional language, which purportedly helps to convey an innovative idea’s originality. Our analysis examines the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies. We find promotional language in a grant proposal is associated with up to a doubling in its probability of being funded, with a grant’s intrinsic innovativeness, and with its predicted citation impact and productivity. Lastly, a computer experiments that substitute a grant’s promotional language with neutral synonyms indicates that promotional language may communicate the merits of ideas through cognitive activation.

This event will not be recorded.

https://www.isi.edu/events/

Speaker Bio

Brian Uzzi the Richard L. Thomas Distinguished Professor of Leadership at the Kellogg School of Management, Northwestern University. He also is Co-Director of the Northwestern University Institute on Complex Systems and Data Science (NICO), holds professorship in sociology and the McCormick School of Engineering, and writes a column on AI and business for Forbes.

Brian’s work focuses on the link between social networks and human achievement and the role of AI in mind + machine partnerships.

Brian has been awarded over 30 teaching and research prizes worldwide, including the Euler Award. He has been on the faculties of Harvard, INSEAD, University of Chicago, and Berkeley, and is a Fellow of the Network Science Society. His work has been funded by DARPA, NSF, and other foundations, is widely cited, and appears frequently in major media outlets worldwide.

Before entering science, Brian worked as a carpenter and a musician. His PhD is from Stony Brook University in sociology.

http:www.kellogg.northwestern.edu/faculty/uzzi