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Cited by 405Labor market dynamics and wage inequalityDigital Economy and Work TransformationEthics and Social Impacts of AI

Economics of Artificial Intelligence: Implications for the Future of Work

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Ernst, Ekkehardt, Merola, Rossana, Samaan, Daniel·2019·IZA Journal of Labor Policy
DOI 10.2478/izajolp-2019-0004
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Abstract

The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job loss and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a widespread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policies are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy, and help share the benefits of productivity growth through the combination of profit sharing, (digital) capital taxation, and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from AI, provided that policymakers and social partners take the particular characteristics of these new technologies into account.

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  • Ernst et al. (2019) conclude that AI is likely to play out in ways different from previous waves, by increasing productivity and potentially creating more inclusive growth, provided correct educational measures are taken in countries that are part of globalised labour chains.

    “In an important review of the literature, which combines a historical approach with a task-focused one, Ernst et al. (2019) conclude that AI in fact is likely to play out in ways different from previous waves, by increasing productivity and potentially creating more inclusive growth, provided correct educational measures are taken in countries that are part of globalised labour chains.”

    From Artificial intelligence and work: a critical review of recent research from the social sciences (2024) · cites this paper as Ernst et al. 2019

  • In low- and middle-income countries (LMICs), the risk of job loss due to AI is even higher than in advanced economies, with risks being 69% in India, 72% in Thailand, 77% in China, and 85% in Ethiopia.

    “In low- and middle-income countries (LMICs), the risk of job loss due to AI is even higher than in advanced economies, with risks being 69 % in India, 72 % in Thailand, 77 % in China, and 85 % in Ethiopia (Ernst et al., 2019).”

    From Impacts of generative artificial intelligence on the future of labor market: a systematic review (2025) · cites this paper as Ernst et al., 2019

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2 of the 77 references couldn’t be matched to a known paper.

Research works printed but not linked: 8

  1. ---; (2018b): Economic Policy for Artificial Intelligence. NBER Working Paper No. 24690. Cambridge, MA: National Bureau of Economic Research.
  2. ---; D. Dorn; L. Katz; C. Patterson; J. Van Reenen (2017a): Concentrating on the Decline in Labor's Share. American Economic Review Papers and Proceedings 107(5), 180-185.
  3. ---; (2015b): Learning by Doing: The Real Connection Between Innovation, Wages, and Wealth. New Haven: Yale University Press.
  4. Culey, S. (2012): Transformers: Supply Chain 3.0 and how Automation will Transform the Rules of the Global Supply Chain. The European Business Review (Online).
  5. ---; Chentouf, L. (2014): Work Organisation and Incentives. Global and Local Economies Review 18(1), 103-135.
  6. Furman, J.; R. Seamans (2018): AI and the Economy. NBER Working Paper No. 24689. Cambridge, MA: National Bureau of Economic Research.
  7. Logg, J. M.; J. A. Minson; D. A. Moore (2018): Algorithm Appreciation: People Prefer Algorithmic to Human Judgment. Harvard Business School Working Paper No. 17-086. Cambridge, MA: Harvard University.
  8. UNCTAD. (2016): Robots and Industrialization in Developing Countries. Policy Brief No. 50. Geneva: United Nations Conference on Trade and Development.

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Authors
Ernst, E., Merola, R., & Samaan, D.
Affiliations
  • Research Department, International Labour Organisation , Route des Morillons 4, 1211 Geneva , Switzerland
  • International Labour Organization (CH)
ORCID
Samaan, Daniel
Venue
IZA Journal of Labor Policy
Publisher
Walter de Gruyter GmbH
Published
2019-06-01
Volume
9
Issue
1
ISSN
2193-9004 (ISSN-L)
DOI
10.2478/izajolp-2019-0004
OpenAlex
W2969615692
Cited by
405
References
77
Citations by year
2026: 39 · 2025: 84 · 2024: 96 · 2023: 61 · 2022: 52 · 2021: 36 · 2020: 30 · 2019: 7
FWCI
39.01
Type
journal article
Language
en
Open access
Licence
Locations
  • IZA Journal of Labor Policy (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Econstor (Econstor) (submittedVersion, cc-by)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
  • Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
artificial intelligence, future of work, job displacement, inequality, productivity growth, automation, robotization, low-skilled workers, skills policy, digital economy regulation, market concentration, data protection, profit sharing, working time reduction, developing countries, technological change

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