By Ajay Agrawal, Joshua Gans, and Avi Goldfarb
Artificial intelligence (AI) technologies have advanced rapidly over the last several years. As the technology continues to improve, it may have a substantial impact on the economy with respect to productivity, growth, inequality, market power, innovation, and employment. In 2016, the White House put out several reports emphasizing this potential impact. Despite its importance, there is little economics research on the topic. The research that exists is derived from past technologies (such as factory robots) that capture only part of the economic reach of AI. Without a better understanding of how AI might impact the economy, we cannot design policy to prepare for these changes. To address these challenges, the National Bureau of Economic Research held its first conference on the Economics of Artificial Intelligence in September 2017 in Toronto, with support from the NBER Economics Digitization Initiative, the Sloan Foundation, the Canadian Institute for Advanced Research, and the University of Toronto’s Creative Destruction Lab. The purpose of the conference was to set the research agenda for economists working on AI. The invitation emphasized these points as follows:
“The context is this: imagine back to 1995 when the internet was about to begin transforming industries. What would have happened to economic research into that revolution had the
leading economists gathered to scope out a research agenda at that time? Today, we are facing the same opportunity with regard to AI. This time around we are convening a group of 30
leading economists to scope out the research agenda for the next 20 years into the economics of AI.””
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