Ideas Made to Matter
Study: Generative AI helps inexperienced workers
Less-experienced contact center agents become more productive with assistance from generative artificial intelligence, a new study finds.
Jun 26, 2023
Faculty
Danielle Li
Support Staff
Get in Touch
Title
About
Academic Groups
Academic Area
Danielle Li is an Associate 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.
Honors
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 news stories of 2022
From “smart skills” to digital marketing trends, here are the stories readers were drawn to this year.
Dec 5, 2022
Media Highlights
Press
Source:
The Conversation
The progress of women in the workplace is at a standstill. How can we br...
Women are promoted less than men because they are deemed to have less leadership potential than men.
Press
Source:
Forbes
Generative AI’s growth bodes well for Microsoft, ChatGPT
“One can imagine various policies that both firms and regulators can take regarding how to address how AI is used."
Press
Source:
Wired
Should you get paid for teaching a chatbot to do your job?
“Now data can be used to solve other people's problems ... I think it's really important to find a way to measure and compensate that.”
Press
Source:
Bloomberg
AI really can boost productivity, especially for lowest-skilled workers
Workers who were given access to generative artificial intelligence tools became 14% more productive on average than those who were not.
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
- Aug 14-Oct 1, 2024
- Jun 5-Jul 23, 2024
- Mar 13-Apr 30, 2024
- Nov 20, 2024-Jan 28, 2025