Erik Brynjolfsson
Affiliated Faculty • DEL Advisory Group • Leadership
Technology is not destiny. We shape our destiny. Just as the earlier generation of managers needed to redesign their factories, we’re going to need to reinvent our organization and even our whole economic system.
Director, Stanford Digital Economy Lab | Jerry Yang and Akiko Yamazaki Professor and Senior Fellow, Stanford Institute for Human-Centered AI (HAI)
Erik Brynjolfsson is one of the world’s leading experts on the economics of technology and artificial intelligence. He is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), and Director of the Stanford Digital Economy Lab. He also is the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR), Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and a Research Associate at the National Bureau of Economic Research (NBER).
One of the most-cited authors on the economics of information, Brynjolfsson was among the first researchers to measure productivity contributions of IT and the complementary role of organizational capital and other intangibles.
Brynjolfsson leads Stanford’s work on Transformative AI—systems poised to rapidly reshape productivity, labor markets, and prosperity. He is developing the research agenda, tools, and policy frameworks to help ensure this shift benefits society, bringing together economists, technologists, and social scientists to rethink economics for the AI age.
Brynjolfsson has authored nine books including the bestsellers The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies, and Machine, Platform, Crowd: Harnessing Our Digital Future, and published more than 100 academic articles and five patents. He holds Bachelors and Masters degrees from Harvard University in applied mathematics and decision sciences and a PhD from MIT in managerial economics. Brynjolfsson’s work has shaped public policy, business strategy, and academic thinking around the world.
Photo credit: Nikki Ritcher
Why traditional economic measures miss billions in value
Coding After Coders: The End of Computer Programming as We Know It
All work
The Consumer Welfare Effects of Online Ads: Evidence from a Nine-Year Experiment
GDP-B: Measuring Well-Being
Suitability for Machine Learning Rubric
How Many Americans Work Remotely? A Survey of Surveys and Their Measurement Issues
Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce
Skills and tasks demand forecasting
Helping Small Businesses Become More Data-Driven: A Field Experiment on eBay
Will Generative Artificial Intelligence Deliver on Its Promise in Health Care?
The Digital Welfare of Nations: New Measures of Welfare Gains and Inequality
Robot Hubs: The Skewed Distribution of Robots in US Manufacturing
The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments
A Causal Test of the Strength of Weak Ties
AI adoption in America: Who, what, and where
Do Computers Reduce the Value of Worker Persistence?
Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis
Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey
Learning Occupational Task-Shares Dynamics for the Future of Work
Toward understanding the impact of artificial intelligence on labor
Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform