Education for the future: an empirical approach to measuring the effect of automation on university outcomes

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Tony Martini Michael Jones

Abstract

By Tony Martini, Economics


Advisor: Michael Jones


Presentation ID: AM_D39


Abstract: This study suggests new methods of measuring the effectiveness of universities in protecting students from the impact of automation on the labor market. Using US government data on occupational activities and traditional measures of university outcomes, we produce a ranking of college majors by their susceptibility to automation and determine correlations between predicted traditional and automation-based outcomes. These are combined into a complete metric for the "automation resistance" of a university. Using an approach centered on distinctly human skills, occupational activities can be ranked by their automation resistance. Institutions which develop student skills with a focus on automation resistance should likewise demonstrate greater long-term viability. We demonstrate this methodology through a case study using data from the University of Cincinnati.

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AM Poster Session -- Great Hall -- D: New Frontiers