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Digitalization and the future of work: Macroeconomic consequences

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  • Arntz, Melanie
  • Gregory, Terry
  • Zierahn, Ulrich

Abstract

Computing power continues to grow at an enormous rate. Simultaneously, more and better data is increasingly available and Machine Learning methods have seen significant breakthroughs in the recent past. All this pushes further the boundary of what machines can do. Nowadays increasingly complex tasks are automatable at a precision which seemed infeasible only few years ago. The examples range from voice and image recognition, playing Go, to self-driving vehicles. Machines are able to perform more and more manual and also cognitive tasks that previously only humans could do. As a result of these developments, some argue that large shares of jobs are "at risk of automation", spurring public fears of massive job-losses and technological unemployment. This chapter discusses how new digital technologies might affect the labor market in the near future. First, the chapter discusses estimates of automation potentials, showing that many estimates are severely upward biased because they ignore that workers in seemingly automatable occupations already take over hard-to-automate tasks. Secondly, it highlights that these numbers only refer to what theoretically could be automated and that this must not be equated with job-losses or employment effects - a mistake that is done often in the public debate. Thirdly, the chapter develops scenarios on how digitalization is likely to affect the German labor market in the next five years and derives implications for policy makers on how to shape the future of work. Germany is an interesting case to study, as it is a developed country at the technological frontier. In particular, the main challenge will not be the number, but the structure of jobs and the corresponding need for supply side adjustments to meet the shift in demand both within and between occupations and sectors.

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  • Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the future of work: Macroeconomic consequences," ZEW Discussion Papers 19-024, ZEW - Leibniz Centre for European Economic Research.
  • Handle: RePEc:zbw:zewdip:19024
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    2. Ashraf Elsafty & Ahmed Elzeftawy, 2023. "Towards Effective Mitigation of the Digital Transformation and COVID-19 Risk on Unemployment in Mobile Operators in Egypt," International Journal of Business and Management, Canadian Center of Science and Education, vol. 17(2), pages 123-123, February.
    3. Kawecka Magdalena, 2023. "Evaluation of the Labour Market Situation of Young People in EU Countries – The Multiple Regression Approach," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 27(3), pages 35-58, September.
    4. Uma RANI & Damian GRIMSHAW, 2019. "Introduction: What does the future promise for work, employment and society?," International Labour Review, International Labour Organization, vol. 158(4), pages 577-592, December.
    5. Gravina, Antonio Francesco & Foster-McGregor, Neil, 2020. "Automation, globalisation and relative wages: An empirical analysis of winners and losers," MERIT Working Papers 2020-040, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    6. Gautam Dutta & Ravinder Kumar & Rahul Sindhwani & Rajesh Kr. Singh, 2021. "Digitalization priorities of quality control processes for SMEs: a conceptual study in perspective of Industry 4.0 adoption," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1679-1698, August.
    7. Hunt, Wil & Sarkar, Sudipa & Warhurst, Chris, 2022. "Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders," Research Policy, Elsevier, vol. 51(2).
    8. Óscar. R. González-López & María Buenadicha-Mateos & M. Isabel Sánchez-Hernández, 2021. "Overwhelmed by Technostress? Sensitive Archetypes and Effects in Times of Forced Digitalization," IJERPH, MDPI, vol. 18(8), pages 1-20, April.
    9. Samantha Joy Cinco, 2021. "Companion or Substitution? Automation and Digitisation in the Workplace," Journal of Entrepreneurship and Innovation in Emerging Economies, Entrepreneurship Development Institute of India, vol. 7(2), pages 263-268, July.

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    More about this item

    Keywords

    Automation; Digitalization; Unemployment; Inequality;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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