معرفی
Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh, within the Department of Informatics and Networked Systems. His research focuses on the complexity of AI, the future of work, and socio-economic consequences of technological change, particularly examining genotypic skill-level processes impacting individuals and society. He holds a PhD from MIT’s Media Lab, with postdoctoral work at MIT IDSS and IDE, and a Master’s in Applied Mathematics from the University of Vermont, where he contributed to the Computational Story Lab.
Frank’s work combines labor research with AI implications, aiming to inform societal understanding of AI’s impact. Key interests include technological unemployment, urban economic resilience, and policy frameworks for green job transitions. His recent publications explore topics like AI exposure and unemployment risk, behavioral networks in urban systems, and geographic barriers to fossil fuel worker retraining.
Frank’s academic background bridges computational methods and social science, with a focus on large-scale data analysis and policy-relevant research. His work has been applied to advise institutions like the Canadian House of Commons on AI labor impacts and to develop tools like the Course-Skill Atlas for aligning education with workforce needs.
