Robot Census: Gathering Data to Improve Policymaking on New Technologies

Robert Seamans
By Robert Seamans
There is understandable excitement about the impact that new technologies like artificial intelligence (AI) and robotics will have on our economy. In our everyday lives, we already see the benefits of these technologies: when we use our smartphones to navigate from one location to another using the fastest available route or when a predictive typing algorithm helps us finish a sentence in our email. At the same time, there are concerns about possible negative effects of these new technologies on labor. The Council of Economic Advisers of the past two Administrations have addressed these issues in the annual Economic Report of the President (ERP). For example, the 2016 ERP included a chapter on technology and innovation that linked robotics to productivity and growth, and the 2019 ERP included a chapter on artificial intelligence that discussed the uneven effects of technological change. Both these chapters used data at highly aggregated levels, in part because that is the data that is available. As I’ve noted elsewhere, AI and robots are everywhere, except, as it turns out, in the data.

To date, there have been no large scale, systematic studies in the U.S. on how robots and AI affect productivity and labor in individual firms or establishments (a firm could own one or more establishments, which for example could be a plant in a manufacturing setting or a storefront in a retail setting). This is because the data are scarce. Academic researchers interested in the effects of AI and robotics on economic outcomes have mostly used aggregate country and industry-level data. Very recently, some have studied these issues at the firm level using data on robot imports to France, Spain, and other countries. I review a few of these academic papers in both categories below, which provide early findings on the nuanced role these new technologies have on labor. Thanks to some excellent work being done by the U.S. Census Bureau, however, we may soon have more data to work with. This includes new questions on robot purchases in the Annual Survey of Manufacturers and Annual Capital Expenditures Survey and new questions on other technologies including cloud computing and machine learning in the Annual Business Survey.

While these new data are a promising step, there is still a need for a large-scale survey of technology use across multiple sectors of the economy. Congress should fund the U.S. Census Bureau to collect this data. The work that Census has done so far—for example by collecting data on the purchase and use of robotics in the manufacturing sector, via its Annual Survey of Manufacturing—provides a blueprint for how this can be done across other sectors of the economy. With better data, researchers will be able to measure the effects of these technologies on a range of issues including productivity, employment, training, inequality and regional competitiveness, and policy makers will be able to develop well-informed policy—or tweak, update, or eliminate existing policy.

Read the full Brookings Institution article
Robert Seamans is Associate Professor of Management and Organizations.