Citizen attitudes about job replacement by robotic automation

Abstract

This study explores the factors influencing citizen attitudes about job replacement by robotic automation and policy options addressing the replacement effect. To this end, 2017 American Trends Panel Wave data from the Pew Research Center are analyzed. The juxtaposition of enthusiasm and concern about the impacts of job replacement by robotic automation is captured in a bi-dimensional view of citizen attitudes, as manifested in four attitudinal categories: optimistic (high enthusiasm and low worry), pessimistic (low enthusiasm and high worry), skeptical (low enthusiasm and low worry), and hybrid (high enthusiasm and high worry). A regression-based analysis is used to predict which attitudinal category an individual belongs to and the degree to which he or she supports certain policy options (guaranteed income, robot quotas, extra pay for human interaction, and a national program for displaced workers) according to his or her awareness, perceived likelihood, and expectation of positive outcomes of job replacement. This analysis reveals that attitudes differ considerably based on ideology and partisanship.