Artificial intelligence impact on occupations and workforce
Author(s)Kansu, Hazal Mine.
Massachusetts Institute of Technology. Institute for Data, Systems, and Society.
Technology and Policy Program.
Geoffrey G. Parker.
MetadataShow full item record
Recent developments in machine learning (ML) have persuaded researchers that automated technologies without human intervention may transform occupations across the economy. My research seeks to assess how and where ML will affect the workforce. I extend the ideas of Brynjolfsson, Mitchell, and Rock (2018), who assess each task in the economy for its Suitability for Machine Learning (SML). This paper builds on their summary statistics to provide a more detailed analysis of where ML is likely to have its greatest impact in the economy. Combining their technological suitability data with labor market data, this paper suggests a policy model for better planning labor mobility and allocation of human resources in the face of upcoming technological changes.
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 72-76).
DepartmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society; Technology and Policy Program
Massachusetts Institute of Technology
Institute for Data, Systems, and Society., Technology and Policy Program.