IDEAS home Printed from https://ideas.repec.org/p/ess/wpaper/id12798.html
   My bibliography  Save this paper

Economic Policy for Artificial Intelligence

Author

Listed:
  • Avi Goldfarb
  • Joshua Gans
  • Ajay Agrawal

Abstract

Recent progress in artificial intelligence (AI) – a general purpose technology affecting many industries - has been focused on advances in machine learning, which we recast as a quality -adjusted drop in the price of prediction. How will this sharp drop in price impact society? Policy will influence the impact on two key dimensions: diffusion and consequences. First, in addition to subsidies and IP policy that will influence the diffusion of AI in ways similar to their effect on other technologies, three policy categories - privacy, trade, and liability - may be uniquely salient in their influence on the diffusion pat terns of AI. Second, labor and antitrust polic ies will influence the consequences of AI in terms of employment, inequality, and competition.

Suggested Citation

  • Avi Goldfarb & Joshua Gans & Ajay Agrawal, 2018. "Economic Policy for Artificial Intelligence," Working Papers id:12798, eSocialSciences.
    • Handle: RePEc:ess:wpaper:id:12798
    Note: Institutional Papers
    as

    Download full text from publisher

    File URL: http://www.esocialsciences.org/Articles/show_Article.aspx?acat=InstitutionalPapers&aid=12798
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Mitchell Hoffman & Lisa B Kahn & Danielle Li, 2018. "Discretion in Hiring," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(2), pages 765-800.
    2. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    3. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    4. Petra Moser, 2005. "How Do Patent Laws Influence Innovation? Evidence from Nineteenth-Century World's Fairs," American Economic Review, American Economic Association, vol. 95(4), pages 1214-1236, September.
    5. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    6. Heidi L. Williams, 2016. "Intellectual Property Rights and Innovation: Evidence from Health Care Markets," Innovation Policy and the Economy, University of Chicago Press, vol. 16(1), pages 53-87.
    7. Jerry R. Green & Suzanne Scotchmer, 1995. "On the Division of Profit in Sequential Innovation," RAND Journal of Economics, The RAND Corporation, vol. 26(1), pages 20-33, Spring.
    8. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    9. Alberto Galasso & Hong Luo, 2018. "Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 493-504, National Bureau of Economic Research, Inc.
    10. Mitsuru Igami, 2017. "Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo," Papers 1710.10967, arXiv.org, revised Mar 2018.
    11. Avi Goldfarb & Catherine Tucker, 2012. "Privacy and Innovation," NBER Chapters, in: Innovation Policy and the Economy, Volume 12, pages 65-89, National Bureau of Economic Research, Inc.
    12. Josh Lerner & Scott Stern, 2016. "Innovation Policy and the Economy, Volume 16," NBER Books, National Bureau of Economic Research, Inc, number lern15-1.
    13. Mitsuru Igami, 0. "Artificial intelligence as structural estimation: Deep Blue, Bonanza, and AlphaGo," Econometrics Journal, Royal Economic Society, vol. 23(3), pages 1-24.
    14. Nicholas Crafts, 2004. "Steam as a general purpose technology: A growth accounting perspective," Economic Journal, Royal Economic Society, vol. 114(495), pages 338-351, April.
    15. Betsey Stevenson, 2018. "Artificial Intelligence, Income, Employment, and Meaning," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 189-195, National Bureau of Economic Research, Inc.
    16. David Autor & David Dorn & Lawrence F Katz & Christina Patterson & John Van Reenen, 2020. "The Fall of the Labor Share and the Rise of Superstar Firms [“Automation and New Tasks: How Technology Displaces and Reinstates Labor”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 645-709.
    17. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    18. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
    19. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    20. Hal Varian, 2018. "Artificial Intelligence, Economics, and Industrial Organization," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 399-419, National Bureau of Economic Research, Inc.
    21. Matt Taddy, 2018. "The Technological Elements of Artificial Intelligence," NBER Working Papers 24301, National Bureau of Economic Research, Inc.
    22. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    23. Fiona Scott Morton & Carl Shapiro, 2016. "Patent Assertions: Are We Any Closer to Aligning Reward to Contribution?," Innovation Policy and the Economy, University of Chicago Press, vol. 16(1), pages 89-133.
    24. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    25. Matt Taddy, 2018. "The Technological Elements of Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 61-87, National Bureau of Economic Research, Inc.
    26. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    27. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    28. Jason Furman & Robert Seamans, 2019. "AI and the Economy," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 161-191.
    29. David, Paul A, 1990. "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox," American Economic Review, American Economic Association, vol. 80(2), pages 355-361, May.
    30. Jason Furman, 2018. "Should We Be Reassured If Automation in the Future Looks Like Automation in the Past?," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 317-328, National Bureau of Economic Research, Inc.
    31. Joshua S. Gans, 2018. "Self-Regulating Artificial General Intelligence," NBER Working Papers 24352, National Bureau of Economic Research, Inc.
    32. Manuel Trajtenberg, 2018. "Artificial Intelligence as the Next GPT: A Political-Economy Perspective," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 175-186, National Bureau of Economic Research, Inc.
    33. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    34. Trajtenberg, Manuel, 2018. "AI as the next GPT: a Political-Economy Perspective," CEPR Discussion Papers 12721, C.E.P.R. Discussion Papers.
    35. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1169-1213.
    36. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    37. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, October.
    38. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    39. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Introduction to "The Economics of Artificial Intelligence: An Agenda"," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 1-19, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    2. Bernardo S Buarque & Ronald B Davies & Ryan M Hynes & Dieter F Kogler, 2020. "OK Computer: the creation and integration of AI in Europe," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 175-192.
    3. Dominic Chalmers & Niall G. MacKenzie & Sara Carter, 2021. "Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution," Entrepreneurship Theory and Practice, , vol. 45(5), pages 1028-1053, September.
    4. J. Klinger & J. Mateos-Garcia & K. Stathoulopoulos, 2018. "Deep learning, deep change? Mapping the development of the Artificial Intelligence General Purpose Technology," Papers 1808.06355, arXiv.org.
    5. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    6. Xueyuan Gao & Hua Feng, 2023. "AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity," Sustainability, MDPI, vol. 15(11), pages 1-21, June.
    7. Alexander Kopka & Dirk Fornahl, 2024. "Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases," Small Business Economics, Springer, vol. 62(1), pages 63-85, January.
    8. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    9. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    10. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    11. Johnson, Prince Chacko & Laurell, Christofer & Ots, Mart & Sandström, Christian, 2022. "Digital innovation and the effects of artificial intelligence on firms’ research and development – Automation or augmentation, exploration or exploitation?," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    12. Martin Obschonka & David B. Audretsch, 2020. "Artificial intelligence and big data in entrepreneurship: a new era has begun," Small Business Economics, Springer, vol. 55(3), pages 529-539, October.
    13. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
    14. Aránzazu Guillán Montero & David Le Blanc, 2019. "Lessons for Today from Past Periods of Rapid Technological Change," Working Papers 158, United Nations, Department of Economics and Social Affairs.
    15. Lynn Wu & Bowen Lou & Lorin Hitt, 2019. "Data Analytics Supports Decentralized Innovation," Management Science, INFORMS, vol. 65(10), pages 4863-4877, October.
    16. Eric J. Bartelsman, 2019. "From New Technology to Productivity," European Economy - Discussion Papers 113, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    17. Seth G. Benzell & Erik Brynjolfsson, 2019. "Digital Abundance and Scarce Genius: Implications for Wages, Interest Rates, and Growth," NBER Working Papers 25585, National Bureau of Economic Research, Inc.
    18. Stefano Bianchini & Moritz Muller & Pierre Pelletier, 2020. "Deep Learning in Science," Papers 2009.01575, arXiv.org, revised Sep 2020.
    19. Kopka, Alexander & Grashof, Nils, 2022. "Artificial intelligence: Catalyst or barrier on the path to sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    20. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.

    More about this item

    Keywords

    Artificial Intelligence; Economy; technology; inequality; labour; competition;
    All these keywords.

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ess:wpaper:id:12798. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Padma Prakash (email available below). General contact details of provider: http://www.esocialsciences.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.