I study what happens when organizations and industries rapidly adopt new technologies. I primarily use qualitative methods (interviewing, observation, surveys, and archival research) to understand why some workers resist new technologies; how management practices influence technology outcomes; and what role organizational and governmental policies play in shaping the decisions organizations and workers make about using new technologies.
My research aims to inform technology and labor management strategies, technology governance frameworks, and theories of technological change, especially change that happens in the workplace. I present the results of the research in academic and practitioner-oriented outlets (see the Publications and Presentations tab for some examples).
I'm currently working as a Project Scientist in the Technology Management Program at the University of California, Santa Barbara College of Engineering. I work with Dr. Matt Beane and study the implementation, management, and labor implications of robotics and automation in the manufacturing and logistics industries.
I am also the principal investigator on a project documenting the histories of two open source software languages via oral histories and archival research, supported by the Sloan Foundation.
Before UCSB, I worked as a postdoc with the rOpenSci Project at UC Berkeley's Institute for Data Science; completed the PhD program and did research at the University of Texas at Austin School of Information; and studied at the University of Pennsylvania's Department of History and Sociology of Science.
For people considering grad school or other paths to studying technology and work: I highly recommend going for it. It's a line of work that has given me the opportunity to work and/or interact with healthcare practitioners, ecologists, economists, warehouse workers, municipal public servants, software engineers, astronomers, management executives, and federal government officials. The similarities and differences in how they approach new technologies are plentiful, complex, and only get more interesting as technologies change. Please send me an email if you need ideas for where to start.
Technology and work
Technology and the future of work
Automation (A.I./robotics), management, and labor
Computer-supported cooperative work
Data science studies
History and sociology of science and technology