Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Comment
  • Published:

Track how technology is transforming work

Nature volume 544, pages 290–292 (2017)Cite this article

Subjects

Without data on how artificial intelligence is affecting jobs, policymakers will fly blind into the next industrial revolution, warn Tom Mitchell and Erik Brynjolfsson.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

References

  1. National Academies of Sciences, Engineering, and Medicine. Information Technology and the U.S. Workforce: Where Are We and Where Do We Go from Here? (National Academies Press, 2017).

  2. Katz, L. F. & Krueger, A. B. The Rise and Nature of Alternative Work Arrangements in the United States, 1995–2015 NBER Working Paper No. 22667 (National Bureau of Economic Research, 2016); available at http://go.nature.com/2nnusoe

  3. Abraham, K. G., Haltiwanger, J. C., Sandusky, K. & Spletzer, J. R. Measuring the Gig Economy: Current Knowledge and Open Issues (paper presented at NBER Conference on Research in Income and Wealth: Measuring and Accounting for Innovation in the 21st Century, Washington DC 10–11 March 2017); available at http://go.nature.com/2ohelvc

  4. McAfee, A. & Brynjolfsson, E. Harvard Bus. Rev. 90, 61–67 (2012).

    Google Scholar 

  5. Brynjolfsson, E. & McElheran, K. Am. Econ. Rev. 106, 133–139 (2016).

    Article  Google Scholar 

  6. Baicker, K. et al. N. Engl. J. Med. 368, 1713–1722 (2013).

    Article  CAS  Google Scholar 

  7. Arrow, K. J. in The Rate and Direction of Inventive Activity: Economic and Social Factors (ed. National Bureau Committee for Economic Research) 609–626 (Princeton Univ. Press, 1962); available at http://go.nature.com/2omibrh

Download references

Author information

Authors and Affiliations

  1. Tom Mitchell is professor of machine learning at Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.,

    Tom Mitchell

  2. Erik Brynjolfsson is professor of management at the Massachusetts Institute of Technology (MIT) and director of the MIT Initiative on the Digital Economy in Cambridge, Massachusetts, USA.,

    Erik Brynjolfsson

Authors
  1. Tom Mitchell
    View author publications

    Search author on:PubMed Google Scholar

  2. Erik Brynjolfsson
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Erik Brynjolfsson.

Additional information

Tweet Follow @NatureNews

Related links

Related links

Related links in Nature Research

There is a blind spot in AI research 2016-Oct-13

Anticipating artificial intelligence 2016-Apr-26

Robotics: Ethics of artificial intelligence 2015-May-27

Nature Insight: Machine intelligence

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mitchell, T., Brynjolfsson, E. Track how technology is transforming work. Nature 544, 290–292 (2017). https://doi.org/10.1038/544290a

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/544290a

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing