Kevin W. Lee

OVERVIEW

My research concerns the future of work and organizing. I have specifically been asking how we might go about adapting to this future even as it has threatened valued parts of our past and present. Many of my studies have investigated this question while examining how the recent push toward economic progress and rationality – such as the increasing orientation toward technologies like artificial intelligence (AI) – has collided with existing work and organizational arrangements, sparking concern about how we might move forward. Along the way, I have been focusing on how we have been culling between what we have recognized as worthy enough to take with us as opposed to leave behind. In so asking, my research builds on studies spanning back to the founding of social scientific inquiry. This scholarship weighed what we were gaining against what we were losing at the dawn of the twentieth century, focusing on disruptions like the rationalization of work, the division of labor, and the monetization of social life. Taking inspiration from these classics, as well as from recent study across social scientific fields like organization theory and sociology, I have attempted to clarify what has been happening today in this new era of change. To do so, I have primarily used inductive qualitative methods, ranging from ethnography to interviews, to investigate how people on the frontier of the future have been dealing with these transformations to work and organizing.

 

KEYWORDS

future of work and organizing

technology, innovation, & entrepreneurship

worth, evaluation, & social inequality

the lived experience of organizations & institutions

qualitative methods (e.g., ethnography, interviews)

 

DISSERTATION

Augmenting or Automating? Breathing Life into the Uncertain Promise of Artificial Intelligence
Committee: Beth Bechky (chair), Paul DiMaggio, Hila Lifshitz-Assaf, Damon Phillips

 

While ethnographically studying a startup developing an artificial intelligence (AI) technology, I puzzled over the phenomenon of “occupational cannibalization”: the fact that occupational members who ran the startup – namely, music composers – ended up developing an AI intended to carve away at their community’s work of music composition. Initially, those at the startup developed the AI to keep this work within the hands of members of the occupation, against its complete takeover by machines. This said, the AI started to be used in ways that did not allow for this imagined future. Instead, the people who started to use it – namely, video content producers – were able to produce music for their videos on their own through the AI, instead of having to hire the music composers they traditionally relied on. In other words, and contrary with the initial intentions of those developing the technology, the AI ended up being used to completely replace some of the occupation’s members. However, and as argued by composers at the startup and beyond it, these emerging patterns of use were consistent with hierarchies of worth within the occupation: the work being automated away, given that it was not seen as being “soulful” in the ways that composers cherished, was not seen as worthy enough to be saved by the occupation’s members. The composers both at the startup and beyond thus were willing to relinquish this work, as well as those who did it, across the community’s boundaries to the advance of machines.