University of Pittsburgh

Skill complexity and labor resilience in the future of work

Assistant Professor
Friday, September 25, 2020 - 12:30pm - 1:30pm

Rapidly advancing cognitive technologies, such as artificial intelligence (AI), have the potential to drastically impact modern society and to shape the future of work. Although a given technology impacts demand for only a narrow set of workplace skills, modern empirical work explains employment trends with coarse labor distinctions between cognitive and physical or routine and non-routine work. In this talk, I explore the complex ways that skills and employment undergird labor dynamics in the US. I perform an unsupervised analysis of specific workplace skills as a network whose aggregate and refined topology grant new insights into job polarization and workers' career mobility. Since these inter-skill connections predict career mobility, I construct a map of US occupations that captures worker transition rates between employment opportunities and, in combination with urban employment data, predicts workers' spatial mobility. These refined models that connect workplace skills to both inter-city and intra-city dynamics enable new insights and new input data sources for real-time labor trends at the level of specific technologies and specific workplace skills. I demonstrate how simple measures for skills within a labor market contribute to the differential impact of automation across US cities of different sizes, and how more complicated measures for job connectivity indicate economic resilience to labor shocks, including labor shifts from COVID-19. These results suggest that preparing for AI and the future of work may best be achieved by fostering resilient workforces and adaptable workers

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