Prasanna Tambe, Operations, Information and Decisions, The Wharton School
Abstract: Using data on employer job search, this study demonstrates that employers are seeking algorithmic literacy from workers in a particularly broad class of occupations because familiarity with algorithms in downstream “using” occupations is important for integrating AI and data science into production. The evidence is consistent with the argument that it is more productive to have algorithmic and occupation-specific human capital embodied in the same worker than divided across jobs. These results stand in contrast to data collection, storage, and management technologies, for which most of the human capital is concentrated in the IT labor force. The results suggest that algorithmic literacy exhibits patterns of occupational demand that differ from other data technologies, with implications for education and job design.