Artificial Intelligence at Work: An Ethnography of the Development and Use of Machine Learning for Hiring

Artificial intelligence (AI) technologies increasingly enter complex areas of work that were once solely reserved for human experts. These technologies have attracted significant research and societal interest given their greater autonomy, learning abilities, and inscrutability compared to previous generations. While existing AI debates often oscillate between utopian and dystopian narratives, this dissertation seeks to move beyond these two extremes by unpacking AI at work—the ongoing practices through which AI technologies shape and are shaped by work in organizations. Building on a three-year ethnography of a vendor and their main client that developed and used AI technology for hiring, this dissertation identifies three areas of work that emerged as critical throughout AI’s trajectory in organizations: data work, knowledge work, and values work. Together, these forms of work help to understand how the development and use of AI have profound implications for organizations through standardizing work practices, augmenting knowledge production, and reconfiguring values. Overall, the insights of this dissertation emphasize the need to move beyond the conventional view of AI as a discrete entity with predictable effects by recognizing its negotiated, performative, and evolving nature in organizational life.