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Harms of AI

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  • Daron Acemoglu

Abstract

This essay discusses several potential economic, political and social costs of the current path of AI technologies. I argue that if AI continues to be deployed along its current trajectory and remains unregulated, it may produce various social, economic and political harms. These include: damaging competition, consumer privacy and consumer choice; excessively automating work, fueling inequality, inefficiently pushing down wages, and failing to improve worker productivity; and damaging political discourse, democracy's most fundamental lifeblood. Although there is no conclusive evidence suggesting that these costs are imminent or substantial, it may be useful to understand them before they are fully realized and become harder or even impossible to reverse, precisely because of AI's promising and wide-reaching potential. I also suggest that these costs are not inherent to the nature of AI technologies, but are related to how they are being used and developed at the moment - to empower corporations and governments against workers and citizens. As a result, efforts to limit and reverse these costs may need to rely on regulation and policies to redirect AI research. Attempts to contain them just by promoting competition may be insufficient.

Suggested Citation

  • Daron Acemoglu, 2021. "Harms of AI," NBER Working Papers 29247, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29247
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    Cited by:

    1. Ilan Noy & Tomáš Uher, 2022. "Four New Horsemen of an Apocalypse? Solar Flares, Super-volcanoes, Pandemics, and Artificial Intelligence," Economics of Disasters and Climate Change, Springer, vol. 6(2), pages 393-416, July.
    2. Caselli, Mauro & Fracasso, Andrea, 2021. "Covid-19 and Technology," GLO Discussion Paper Series 1001, Global Labor Organization (GLO).
    3. Janine Berg & Francis Green & Laura Nurski & David A Spencer, 2023. "Risks to job quality from digital technologies: Are industrial relations in Europe ready for the challenge?," European Journal of Industrial Relations, , vol. 29(4), pages 347-365, December.
    4. Alonso, Cristian & Berg, Andrew & Kothari, Siddharth & Papageorgiou, Chris & Rehman, Sidra, 2022. "Will the AI revolution cause a great divergence?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 18-37.
    5. Alessandro Sterlacchini, 2022. "AI Patenting and Employment: Evidence from the World's Top R&D Investors," Working Papers 462, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    6. Kowalewski, Oskar & Pisany, Paweł, 2022. "Banks' consumer lending reaction to fintech and bigtech credit emergence in the context of soft versus hard credit information processing," International Review of Financial Analysis, Elsevier, vol. 81(C).
    7. DELBONO Flavio & REGGIANI Carlo & SANDRINI Luca, 2021. "Strategic data sales to competing firms," JRC Working Papers on Digital Economy 2021-05, Joint Research Centre.
    8. Jeffrey K. Aronson, 2022. "Artificial Intelligence in Pharmacovigilance: An Introduction to Terms, Concepts, Applications, and Limitations," Drug Safety, Springer, vol. 45(5), pages 407-418, May.

    More about this item

    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
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • P16 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Capitalist Institutions; Welfare State

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