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Learn More About Daniel Rock
Daniel Rock, Ph.D., is an assistant professor of Operations, Information, and Decisions at the Wharton School of the University of Pennsylvania. His research is on the economic effects of digital technologies, with a particular emphasis on the economics of artificial intelligence. He has recently worked on studies addressing the types of occupations that are most exposed to machine learning, measuring the value of AI skillsets to employer firms, and adjusting productivity measurement to include investments in intangible assets. His research has been published in various academic journals and featured in outlets such as The New York Times, Wall Street Journal, Bloomberg, Harvard Business Review, and Sloan Management Review. Much of his work involves applying cutting-edge data science techniques to analyze datasets from financial market data sources, online resume sites, and job postings.
Rock is a co-founder, along with Erik Brynjolfsson and Andrew McAfee, of Workhelix, a workforce AI startup where he leads the company’s technology and research efforts.
Rock received his B.S. from the Wharton School of the University of Pennsylvania, and his M.S. and Ph.D. from the Massachusetts Institute of Technology. Between undergraduate and graduate studies, he worked as an Algorithmic Trader at DRW Trading.
Daniel Rock is available to advise your organization via virtual and in-person consulting meetings, interactive workshops and customized keynotes through the exclusive representation of Stern Speakers & Advisors, a division of Stern Strategy Group®.
How to Capitalize on Generative AI
November-December 2023
Daniel Rock on How AI Will Reshape Economies (Audio)
October 20, 2023
Behind the Markets Podcast: Daniel & Anton (Audio)
October 6, 2023
Behind the Markets Podcast: Daniel Rock (Audio)
June 24, 2023
Which Professions Are Threatened by LLMs (Audio)
August 15, 2023
Digital Capital and Superstar Firms
March 4, 2021
How Managers Can Enable AI Talent in Organizations
August 5, 2020
Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence
(Brookings Center on Regulations and Markets, June 2022)
Digital Capital and Superstar Firms
(Hutchins Center on Fiscal and Monetary Policy, March 2021)
Understanding and Addressing the Modern Productivity Paradox
(Governance In An Emerging New World, May 2019)
The Productivity J-Curve: How Intangibles Complement General Purpose Technologies
(American Economic Journal, January 2021)
"The world is full of people…far too many, in fact...who claim they know what they’re talking about regarding generative AI and the implications it may have for organizations and the people working in them. The difference between those people and Dan is that he actually has the authority and credibility to say it. Nobody knows more about the topic than him, and nobody is a more delightful and engaging expert on the topic with which to work. In the first eight months of knowing him we put him in front of our entire firm, and on two occasions, our most senior clients. Every time we looked brilliant for doing so. Highly recommended."