Faculty
Danielle Li is the David Sarnoff Professor of Management of Technology and a Professor at the MIT Sloan School of Management, as well as a Faculty Research Fellow at the National Bureau of Economic Research. Her research interests are in economics of innovation and labor economics, with a focus on how organizations evaluate ideas, projects, and people.
Danielle's work has been published in leading academic journals across a range of fields, including the Quarterly Journal of Economics, Science, and Management Science. In addition, her work has been regularly featured in media outlets such as the Economist, New York Times, and Wall Street Journal.
She has previously taught at the Harvard Business School and the Kellogg School of Management. She holds an AB in mathematics and the history of science from Harvard College and a PhD in economics from MIT.
Featured Publication
"Discretion in Hiring."Hoffman, Mitchell, Lisa Kahn, and Danielle Li. Quarterly Journal of Economics Vol. 133, No. 2 (2018): 765-800. Download paper.
Featured Publication
"Public R&D Investments and Private Sector Patenting: Evidence from NIH Funding Rules."Azoulay, Pierre, Joshua S. Graff Zivin, Danielle Li, and Bhaven N. Sampat. Review of Economic Studies Vol. 86, No. 1 (2019): 117-152.
Benson, Alan M., Danielle Li, and Kelly Shue. Academy of Management Proceedings Vol. 2023, No. 1 (2023).
Brynjolfsson, Erik, Danielle Li, and Lindsey R. Raymond, MIT Sloan Working Paper 6848-23. Cambridge, MA: MIT Sloan School of Management, April 2023. NBER Working Paper 31161.
Agha, Leila, Soomi Kim, and Danielle Li. American Economic Review: Insights Vol. 4, No. 2 (2022): 191-208. Download Preprint.
Joshua Krieger, Danielle Li, and Dimitris Papanikolaou. The Review of Financial Studies Vol. 35, No. 2 (2022): 636–679. Download Preprint.
Artificial intelligence can be useful in the workplace, but humans have to first define what success looks like, according to MIT Sloan’s Danielle Li.
Danielle Li studies how AI impacts work and the workplace. “I’m more interested in how businesses put these tools to use, how they impact the productivity of workers, the type of work they are able to do, and what their careers might look like in an AI-intensive world,” she says.
Author Diane Hamilton took a class at MIT Sloan where Thomas Malone and Danielle Li shared research that "goes beyond the usual AI hype."
AI could narrow gaps by transferring best practices from talented to less talented employees.
We asked 8 MIT Sloan faculty members about their new projects and what they see as the most exciting — and concerning — aspects of the AI boom.
At the moment, the technology may be more of a digital toy. Perhaps, then, high-achieving women are simply better at avoiding distraction.
Over six weeks, you’ll explore the technical and strategic considerations for robust, beneficial, and responsible AI deployment. You’ll examine the various stages of a proprietary ML Deployment Framework and unlock new opportunities by investigating the key challenges and their related impact. Guided by leading experts and MIT academics, you’ll build a toolkit for addressing these challenges within your own organization and context.
