#AcademicRunPlaylist - 4/6/24

It was an active Saturday, but I was still able to fit in some talks for my #AcademicRunPlaylist!

First was the second day of the NBER's economic impacts of WW2 symposium. Standouts for me were the talks by Alexander Field (the economic consequences of US mobilization for WW2), Nicolas Ziebarth (the national war labor board and economic inequality during and after WW2), Bill Collins and Ariell Zimran (beneficiaries of WW2 services and the GI bill), and Valerie Ramey (why didn't the US unemployment rate rise at the end of WW2) https://www.youtube.com/watch?v=lL8E8vru4wE

Next was the NBER race and stratification working group symposium. I particularly liked the talks by Kurt Lavetti (workplace stratification and racial health disparities) and Elizabeth Linos (the effect of white coworkers on black women's careers) https://www.youtube.com/watch?v=xy8onWuK5Ag

Next was a great talk by Claudia Olivetti on the relationship between flexible work, gender norms, parental leave, and career outcomes at the Department of Economics, University of Oxford https://www.youtube.com/watch?v=suxqEAkW6Jo

Next was an important talk by Anandita Pan on the intersection of gender and caste in India at the Boston Study Group https://www.youtube.com/watch?v=MqYyIRHPFuw

Next was an excellent talk by Barbara Petrongolo on the economics of the gender pay gap at Oxford. Petrongolo combines a unique survey of economists' views of the cause of the gender gap in earnings, then demonstrates that the reasons they cite have already been disproved by the literature. She then gets into possible fixes for the short and long term. Highly recommend https://www.youtube.com/watch?v=agTWt7sonUs

Last was a fantastic panel on AI and power at Brown University with Kim Gallon, Suresh Venkatasubramanian, and C. Malik Boykin. There's wonderfully no discussion of AI-hype topics here, instead the discussion focuses on the current harms and opportunities created by algorithmic and data intensive technologies. I also loved the criticism of approaches (like synthetic data) that take a techno-solutionist approach to reducing AI harms. Highly recommend https://www.youtube.com/watch?v=LbQzMrGzzwU