The Digital Economy Lab
The Digital Economy Lab at the Stanford Institute for Human-Centered AI (HAI), co-sponsored by the Stanford Institute for Economic Policy Research, is an interdisciplinary research group studying how digital technologies are transforming work, organizations, and the economy.
An engine for research and education, the Digital Economy Lab brings together an unprecedented group of stakeholders to analyze data, run experiments, develop theories, and provide actionable insights. It is also an integral part of HAI, as its primary hub for conducting research related to the economic implications of technology—and a demonstration of HAI’s multidisciplinary approach to addressing complex problems.
As we venture into uncharted territory with brilliant technologies and applications, the Digital Economy Lab aims to explore how such technologies transform the economy and can create a world of shared prosperity.
The Lab is also deeply committed to outreach. In the coming decades, few topics will be of more consequence to more people than AI, the digital economy, and the intersection of the two. The Lab is intent on lowering the barriers to understanding such topics with accessible, evidence-based information that spans a range of media. We hope that experts and novices alike will find the Lab an engaging, trusted source for addressing profound questions about the changes our world faces.
The Digital Economy Lab is led by Prof. Erik Brynjolfsson, whose research focuses on the economic implications of digital technologies and AI. He is the co-author of nine books, including The Second Machine Age, over 100 academic articles, and five patents. Brynjolfsson joined Stanford in July, 2020, after over 25 years at the Massachusetts Institute of Technology.
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AI and the Future of Work
Understanding the future of the workforce in a rapidly changing global economy. AI and other digital technologies have the potential to radically transform work, including the displacement of workers, the creation of new types of organizations and changes in productivity and performance. This research area investigates the effects of the current, ongoing phase of automation and augmentation of the workforce; the introduction of Ai and robotics on employment, wages, and inequality; and the nature of work in the future.
Measuring the Digital Economy
Creating better methods of measuring the health of an increasing digital economy, as old metrics become less relevant and new tools become available. Gross Domestic Product (GDP), though often used as a proxy for economic well-being, was not designed for this purpose and is inadequate. In our current research, we are building new metrics for measuring changes in consumer well-being that capture the value of currently unmeasured (often free) digital goods and services. By conducting extensive online surveys, we seek to build an index of digital goods and traditional goods that enables us to develop a complement to GDP. Based on a comprehensive measure of economic output, our GDP-B Index will give decision-makers the ability to manage the economy more effectively.
Digital Business Models
Analyzing the new ways to do business via digital and intelligent technologies. Digital technologies change trade-offs and make it possible to create business and economic value in new ways. Digital goods and services can be reproduced at almost zero marginal cost and transmitted almost instantaneously throughout in the world. They eliminate many constraints on business and competition, while creating opportunities for winner-take-most markets. At the same time, digital and intelligent technologies can vastly reduce search and transaction costs, while improving matching of even traditional goods and services. DEL will explore how these new business models operate and what they mean for society, business, and the economy.
Data-driven decision-making and Management Practices
Measuring, predicting and assessing the diffusion of data-driven decision-making
Researchers at DEL have valuable access not only to US Census Data, but also the ability to add questions to the Management and Organizational Practices (MOPS) survey, which includes 50,000 manufacturers in the US, and other related surveys. These surveys are conducted periodically; we are currently in the midst of the 2021 MOPS effort. Research based on this data will help us understand the diffusion of new technologies (AI/ML, Automation/Robotics), changing business practices to enable these technologies, and the impact on workers.
At DEL, we believe that companies building AI technologies need to focus on the human component and impact along with the technical aspects. The insights developed from DEL research can help companies, policymakers, students, and professionals rise to the challenges and opportunities created by digitization and shape our future.
Prof. Erik Brynjolfsson
Director of the Digital Economy Lab. He also holds appointments as a Senior Fellow at Stanford Institute for Human-Centered AI (HAI) and as the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR). He is a Professor, by courtesy, at the Stanford Graduate School of Business and at the Stanford Department of Economics and a Research Associate at the National Bureau of Economic Research (NBER).
The Economics of Technology Professor, Stanford Graduate School of Business; SIEPR Senior Fellow
Professor of Economics, School of Humanities and Sciences Senior Fellow, Stanford Institute for Economic Policy Research
Trione Director of the Stanford Institute for Economic Policy Research, Wayne and Jodi Cooperman Professor of Economics
Associate Professor and W.M. Keck Foundation Faculty Scholar in the Department of Management Science and Engineering
Provost Emeritus, and Patrick Suppes Family Professor in the School of Humanities and Sciences, Stanford University; Denning Co-Director, Stanford Institute for Human-Centered Artificial Intelligence
Associate Professor of Management Science and Engineering and, by Courtesy, of Computer Science and of Electrical Engineering
Professor, Management Science & Engineering, Co-Director, Stanford Technology Ventures Program
Assistant Professor of Economics; Faculty Fellow, Stanford Institute for Economic Policy Research
Sequoia Professor, Computer Science Department; Denning Co-Director, Stanford Institute for Human-Centered Artificial Intelligence
Shirley R. and Leonard W. Ely, Jr. Professor of Humanities and Sciences, Senior Fellow at SIEPR and Professor, by courtesy, of Economics at the Graduate School of Business and of Management Science and Engineering
DEL will be a catalyst for new ideas, experiments, and collaborations—connecting academics, business leaders, practitioners, and policymakers to generate research and insights to inform and educate a diverse community of stakeholders. Our work is made possible by foundations, corporations, and individuals who share our love of data-driven economic analysis and actionable insights.