Kate Kellogg

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Kate Kellogg

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Kate Kellogg is the David J. McGrath Jr Professor of Management and Innovation, a Professor of Business Administration at the MIT Sloan School of Management.

Kate's research focuses on helping knowledge workers and organizations develop and implement Predictive and Generative AI products, on-the-ground in everyday work, to improve decision making, collaboration, and learning. She shows how organizations can gain user acceptance and effective use of intelligent products and services by including users in the technology design process, providing training to give employees the skills they need to work with intelligent technologies, and designing the technologies with employees in mind.

She has authored dozens of articles that have appeared in top journals across the fields of management, organization studies, healthcare, sociology, work and employment, and information systems research. Her research has won awards from the Academy of Management, the American Sociological Association, the Alfred P. Sloan Foundation, the Institute for Operations Research and the Management Sciences, and the National Science Foundation.

Over the past decade, Kate has partnered with for-profit and not-for-profit organizations to help improve collaboration among diverse experts, use technologies to improve internal knowledge sharing, and manage the human aspects of new technology implementation in order to thrive in fast-paced and uncertain contexts.

Before coming to MIT Sloan, Kate worked as a management consultant for Bain & Company and for Health Advances. She received her PhD in organization studies from MIT, her MBA from Harvard, and her BA from Dartmouth in biology and psychology.

 

 

Honors

Kellogg wins Jamieson Prize

Publications

"Don't Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics."

Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan R. Mollick, Fabrizio Dell'Acqua, Edward McFowland III, Francois Candelon, and Karim R. Lakhani, Working Paper. June 2024.

"Triadic Advocacy Work."

Jackson, Summer Rachel, Katherine C. Kellogg. Organization Science Vol. 34, No. 1 (2023): 456-483.

"Why Providing Humans with Interpretable Algorithms May, Counterintuitively, Lead to Lower Decision-making Performance."

DeStefano, Timothy, Katherine C. Kellogg, Michael Menietti, and Luca Vendraminelli, MIT Sloan Working Paper 6797-22. Cambridge, MA: MIT Sloan School of Management, October 2022. WSJ Article.

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