Policy Strategies for Harnessing Productivity Potential of AI in the U.S.
Policy Strategies for Harnessing Productivity Potential of AI in the U.S.
Policy Strategies for Harnessing the Productivity Potential of AI in the U.S.
Despite the emergence of new machine learning technologies capable of diagnosing diseases, understanding speech, or recognizing images, the enormous economic potential of many digital goods and services remains largely untapped. In this brief, scholars propose a set of policy recommendations that could increase productivity growth, make the U.S. more competitive, and reduce income inequality.
Key Takeaways
The pace of measured productivity growth in the United States has slowed over the past two decades, resulting in a massive gulf of potential GDP lost. We estimate that this is equivalent to $4.2 trillion lost for the year 2019.
Failing to properly measure the output of the digital economy and monopolistic behavior by some companies play some role in the slowdown, but the most important factor may be the considerable amount of time and effort required for complementary innovations to keep pace with fundamental technologies like AI.
Policymakers can boost productivity by increasing investments in research and development, expanding immigration of high-skilled labor and reinforcing our education system, and removing many of the legal and regulatory bottlenecks that currently exist to business innovation and entrepreneurship.
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