Videos
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What can machines learn and what does it mean for occupations and the economy?- SumMIT Day 1 -
AI's Impact on Productivity and Innovation
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Research Spotlight: The Impact of LLMs on the Labor Market
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GPTs are GPTs: An Early Look at the Labor Market Impact Potential of LLMs | Daniel Rock
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Massey Dialogues: How at Risk are Jobs to Generative AI
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CODE@MIT 2023 Fireside Panel on Generative AI
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Daniel Rock Discusses the Disruptive Future of Artificial Intelligence on Investing
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Daniel Rock: “Engineering Value: The Returns to Technological Talent and Investments in AI”
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®.
Forge a Powerful Financial Path Forward with This AI Economics Primer
It’s uncertain how AI will affect society, but one thing is sure – AI will have huge impacts on global economies and business competition. How can organizational leaders get up to speed now to bolster their company’s margins for years to come? According to Daniel Rock, Ph.D., Wharton School professor and Stanford Digital Economy Lab fellow, it’s vital for executives to understand where productivity in AI comes from. In this presentation, Rock leverages his unique engineering mindset and background in financial markets to provide leaders with an accessible primer on the effects of AI on monetary systems, both internally and externally. Explaining “what gets you paid in AI,” Rock presents practical tools for measuring and quantifying the real-world economic impacts of today’s leading technologies. Audiences will be empowered to make better decisions to get and stay ahead of competitors through strategic, financially sound AI investment and deployment.
How a Sound AI Strategy Can Empower Your Future Workforce
It’s hard to keep up with all the catchphrases around artificial intelligence and the future of work. Between automation, augmentation, upskilling and reskilling, how can managers and executives break through the buzzwords to create a logical, AI-powered path forward for their organization and its workforce? According to Daniel Rock, Ph.D., Wharton School professor and CTO at Workhelix, AI won’t become the wholesale labor market disruptor some predict, but it’s important for leaders to identify thoughtful implementation strategies. In this informative presentation, Rock outlines an empowering AI-enabled future of work by spotlighting types of occupations most exposed to disruption by machine learning, how to measure the value of AI skillsets, and why productivity growth must be reframed. Audiences will learn practical strategies for zeroing in on the best uses for technologies like generative AI, giving them a framework that supports both tech-enabled organizational efficiency and workforce-friendly jobs models.
Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence
(Brookings Center on Regulations and Markets, June 2022)
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."
