Daniel Rock 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 and the incorporation of machine learning techniques into economic research. 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. Daniel 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. He is also a Fellow at the Stanford Digital Economy Lab and the MIT Initiative on the Digital Economy.

AI2050 Project

Daniel Rock’s AI2050 project aims to utilize artificial intelligence in analyzing economic policies and labor market dynamics as a result of rapid AI advancements and other labor market trends. It will employ AI tools to evaluate unstructured economic data, such as job postings, to measure the impact of AI on job creation and technological dissemination. The project will also explore changing compensation risks and levels for different job types. Lastly, a large language model, fine-tuned on job postings data, will be built and open-sourced, paving the way for a wider variety of economic research in the future.

Project Artifacts

T. Eloundou, S. Manning, P. Mishkin, D. Rock. GPTs are GPTs: Labor market impact potential of LLMs. Science. 2024.