Should Governments Tax Companies’ Use of Robots? Automated Workers, Technological Unemployment, and Wage Inequality Cover Image
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Should Governments Tax Companies’ Use of Robots? Automated Workers, Technological Unemployment, and Wage Inequality
Should Governments Tax Companies’ Use of Robots? Automated Workers, Technological Unemployment, and Wage Inequality

Author(s): Luminita Ionescu
Subject(s): Business Economy / Management, Public Finances, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: robot tax; automated worker; technological unemployment;

Summary/Abstract: I inspect the relevant literature on the relationship between automated workers, technological unemployment, and wage inequality, providing both quantitative evidence on trends and numerous in-depth empirical examples. Building my argument by drawing on data collected from The Boston Consulting Group, eMarketer, MIT Sloan Management Review, Morar Consulting, Narrative Science, National Post, NBR Institute, OECD, Pew Research Center, Squiz, Statista, and YouGov, I performed analyses and made estimates regarding leading advantages of artificial intelligence for international organizations (%), the most important benefit that an artificial intelligence-powered solution should provide (%), jobs with high potential for automation or significant change in task (%), U.S. workers worried they might lose their job to advancing technology (%), U.S. workers who expect artificial intelligence will affect the workforce in the next five years (%), and U.S. workers who say they would strongly oppose/oppose/favor/strongly favor certain policies in the event that robots and computers are capable of doing many human jobs (%). The results of a study based on data collected from 4,200 respondents provide support for my research model. Using the structural equation modeling and employing the probability sampling technique, I gathered and analyzed data through a self-administrated questionnaire.

  • Issue Year: 14/2019
  • Issue No: 2
  • Page Range: 64-69
  • Page Count: 6
  • Language: English