AI exposure predicts unemployment risk: A new approach to technology-driven job loss
Authors:
Morgan R. Frank, Yong-Yeol Ahn, Esteban Moro
Morgan R. Frank
Digital Fellows
Technology’s labor implications are exciting, confusing, and worrying to many. But the Lab is working hard to explore technology’s impact and ground insights in the real world.
Assistant Professor, University of Pittsburgh | Senior Fellow, Microsoft AI Economy Institute
Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh. Additionally, he is a Digital Fellow in the Digital Economy Lab and a Senior Fellow at Microsoft’s AI Economy Institute. Morgan is interested in AI, the future of work, and the complexity of the socio-economic consequences of technological change. Combining labor research with investigations into the nature of AI research and the social or societal implications of AI adoption, Morgan hopes to inform our understanding of AI’s impact.
Morgan has a PhD from MIT’s Media Lab, was a postdoc at MIT IDSS and the IDE, and has a masters degree in applied mathematics from the University of Vermont where he was a member of the Computational Story Lab.
Suitability for Machine Learning Rubric
Researchers:
Erik Brynjolfsson, Daniel Rock, Tom Mitchell, Sarah Bana, Iyad Rahwan, Morgan R. Frank, Max Feng
AI exposure predicts unemployment risk: A new approach to technology-driven job loss
Authors:
Morgan R. Frank, Yong-Yeol Ahn, Esteban Moro
Network constraints on worker mobility
Authors:
Morgan R. Frank, Esteban Moro, Tobin South, Alex Rutherford, Sandy Pentland, Bledi Taska, Iyad Rahwan
Toward understanding the impact of artificial intelligence on labor
Authors:
Morgan R. Frank, David Autor, James E. Bessen, Erik Brynjolfsson, Manuel Cebrian, David J. Deming, Maryann Feldman, Matthew Groh, José Lobo, Esteban Moro, Dashun Wang