Ideas Made to Matter
Generative AI research from MIT Sloan
Ideas about how to best deploy generative artificial intelligence, how it will affect the workforce, and how it should be regulated.
Dec 18, 2023
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Danielle Li
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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.
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Publications
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.
"Potential and the Gender Promotion Gap."
Benson, Alan M., Danielle Li, and Kelly Shue. Academy of Management Proceedings Vol. 2023, No. 1 (2023).
"Generative AI at Work."
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.
"Insurance Design and Pharmaceutical Innovation."
Agha, Leila, Soomi Kim, and Danielle Li. American Economic Review: Insights Vol. 4, No. 2 (2022): 191-208. Download Preprint.
"Missing Novelty in Drug Development."
Joshua Krieger, Danielle Li, and Dimitris Papanikolaou. The Review of Financial Studies Vol. 35, No. 2 (2022): 636–679. Download Preprint.
Recent Insights
Ideas Made to Matter
The top 10 MIT Sloan articles of 2023
Artificial intelligence is everywhere. But it’s humble leadership that leads our list.
Nov 27, 2023
Media Highlights
Press
Source:
The Economist
Why don't women use artificial intelligence?
At the moment, the technology may be more of a digital toy. Perhaps, then, high-achieving women are simply better at avoiding distraction.
Press
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The Wall Street Journal
AI is coming for India's famous tech hub
"Global demand for people is going to decrease. India's share of this decline is less clear, but I am a little pessimistic."
Press
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The Washington Post
AI doesn't have to destroy jobs. It can empower the working class.
Research from Daron Acemoglu, Simon Johnson, Danielle Li, and Mert Demirer is referenced in this article about the effects of AI on workers.
Press
Source:
The Verge
In defense of busywork
Danielle Li said she would celebrate AI tools reducing three hours of labor to one hour of labor.
Executive Education
Executive Education Course
Making AI Work: Machine Intelligence for Business and Society
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.
- Nov 15, 2023-Jan 23, 2024
- Mar 13-Apr 30, 2024
- Aug 14-Oct 1, 2024
- Jun 5-Jul 23, 2024
- Nov 20, 2024-Jan 28, 2025