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Artificial Intelligence in Health Care? Evidence from Online Job Postings

Author

Listed:
  • Avi Goldfarb
  • Bledi Taska
  • Florenta Teodoridis
Abstract
This paper documents a puzzle. Despite the numerous popular press discussions of artificial intelligence (AI) in health care, there has been relatively little adoption. Using data from Burning Glass Technologies on millions of online job postings, we find that AI adoption in health care remains substantially lower than in most other industries and that under 3 percent of the hospitals in our data posted any jobs requiring AI skills from 2015–2018. The low adoption rates mean any statistical analysis is limited. Nevertheless, the adoption we do observe shows that larger hospitals, larger counties, and integrated salary model hospitals are more likely to adopt.

Suggested Citation

  • Avi Goldfarb & Bledi Taska & Florenta Teodoridis, 2020. "Artificial Intelligence in Health Care? Evidence from Online Job Postings," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 400-404, May.
    • Handle: RePEc:aea:apandp:v:110:y:2020:p:400-404
    DOI: 10.1257/pandp.20201006
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    Citations

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    Cited by:

    1. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    2. Joshua S. Gans, 2023. "Artificial intelligence adoption in a competitive market," Economica, London School of Economics and Political Science, vol. 90(358), pages 690-705, April.
    3. Lee, Yong Suk & Kim, Taekyun & Choi, Sukwoong & Kim, Wonjoon, 2022. "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy," Technovation, Elsevier, vol. 118(C).
    4. E. Mark Curtis & Ioana Marinescu, 2023. "Green Energy Jobs in the United States: What Are They, and Where Are They?," Environmental and Energy Policy and the Economy, University of Chicago Press, vol. 4(1), pages 202-237.
    5. Alekseeva, Liudmila & Azar, José & Giné, Mireia & Samila, Sampsa & Taska, Bledi, 2021. "The demand for AI skills in the labor market," Labour Economics, Elsevier, vol. 71(C).
    6. Atkins, Rachel M.B. & Hernández-Lagos, Pablo & Jara-Figueroa, Cristian & Seamans, Robert, 2023. "JUE Insight: What is the impact of opportunity zones on job postings?," Journal of Urban Economics, Elsevier, vol. 136(C).
    7. Jin Liu & Kaizhe Chen & Wenjing Lyu, 2024. "Embracing artificial intelligence in the labour market: the case of statistics," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    8. Ajay Agrawal & Joshua Gans & Avi Goldfarb & Catherine Tucker, 2023. "Introduction to "The Economics of Artificial Intelligence: Health Care Challenges"," NBER Chapters, in: The Economics of Artificial Intelligence: Health Care Challenges, pages 1-7, National Bureau of Economic Research, Inc.
    9. Rathi, Sawan & Majumdar, Adrija & Chatterjee, Chirantan, 2024. "Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

    More about this item

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • 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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