ACADEMIC ARTICLE SUMMARY

AI and the Economy

Article Source: NBER Working Paper 24689, 2018
Publication Date:
Time to Read: 2 minute read
Written By:

 Jason Furman

Jason Furman

ARTICLE SUMMARY

Summary:

Artificial intelligence (AI) and robotics may boost productivity, but might disrupt the labor market. New regulatory and antitrust policies might mitigate harmful effects.

POLICY RELEVANCE

Policy Relevance:

New policies might help ameliorate problems in the labor market caused by AI.

KEY TAKEAWAYS

Key Takeaways:
  • Growth in advanced economies was slower from 2006 to 2016 than from 1996 to 2006; the male labor force participation rate fell from 98 percent in the 1950s to 89 percent in 2016, suggesting that some struggle to find new jobs.
  • Some are concerned that AI will precipitate rapid change, such that there are long periods of time in which large segments of the population are not working.
  • Many economists rely on theoretical models to predict productivity growth related to AI and robotics, due to a lack of data about the use of AI and robotics at the firm level; some early firm-level studies find that robots do increase labor productivity.
  • So far, most AI is used to lower the cost of making predictions through machine learning; this suggests that AI will not have an unprecedented effect on the entire economy, but will disrupt some sectors and workers.
  • Antitrust agencies recognize that the control of large datasets by dominant tech firms might create barriers to competition; requiring that customers be allowed to move their data from one provider to another ("data portability") could help ensure that new firms can enter the market.
  • Universal basic income programs, which provide enough cash to stop people from falling below the poverty line, could address mass joblessness, but might require doubling of basic tax rates.
  • Other proposals to address large-scale unemployment would include expanded employment subsidies (payments to supplement the income of those earning low wages) or guaranteed federal employment.
  • Policymakers could create a new agency to regulate AI, either to advise other agencies or with its own enforcement powers.

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Rob Seamans

About Rob Seamans

Robert Seamans is an Associate Professor at New York University’s Stern School of Business where he teaches courses in game theory and strategy. Professor Seamans’ research focuses on how firms use technology in their strategic interactions with each other, and also focuses on the economic consequences of AI, robotics and other advanced technologies.