Machine learning developers should talk to end users
Machine learning tools only work if people use and trust them. To achieve this, developers and end users should have a back-and-forth conversation.
Faculty
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, and Group Head for the Work and Organization Studies Department.
Kate's research focuses on helping organizations implement new technologies, on-the-ground in everyday work, to improve decision making, collaboration among diverse experts, and learning in a time of rapid digital transformation. She shows how organizations can gain user acceptance of new technologies by including users in the technology design process, providing training to give employees the skills they need to work with new technologies, and designing new technologies with employees in mind.
Kate's current projects examine the collaborative implementation of machine learning-based tools for clinical decision support in healthcare organizations and the implementation of online training for frontline healthcare workers.
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 University, and her BA from Dartmouth College in biology and psychology.
Kellogg, Katherine C. Organization Science (2021): 1-30.
Kellogg, Katherine C., Jenna E. Myers, Lindsay Gainer, Sara J. Singer. Organization Science Vol. 32, No. 1 (2021): 181-209.
Singer, Sarah J., Katherine C. Kellogg, Ari B. Galper, and Deborah Viola. Healthcare Management Review. Forthcoming.
Kellogg, Kate. Wall Street Journal, November 28, 2021.
Kellogg, Katherine C. MIT Sloan Management Review, September 2021.
Altman, Elizabeth J., Katherine C. Kellogg, and David Kiron. In The Power of Ecosystems: Making Sense of the New Reality for Organizations, edited by Stuart Crainer, 12-23. London, UK: Business Ecosystem Alliance, 2021. Access to full eBook.
Machine learning tools only work if people use and trust them. To achieve this, developers and end users should have a back-and-forth conversation.
Insights from experts about how today’s leaders can manage employee needs, organizational culture, technology, and innovation.
Developers must think beyond a project's business benefits and ensure that end users' workflow concerns are addressed.
" ... helping employees to accept new technologies is just as important as making sure the systems work in the first place."
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"The promise of these technologies is that they're going to automate a lot of practices and processes, but they don't do that perfectly."