Outsourcing Attention Management to Human and Artificial Agents in Organizations

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

As the capabilities of artificial intelligence advance, organizations are faced with new opportunities to outsource tasks and decisions about their practices to machines. The introduction of artificially intelligent (AI) assistants to workplaces and their effect on organizational performance has garnered both excitement and concern. While some executives praise AI and laud its value as a solution for organizational problems, other workers fear that artificial intelligence will threaten and displace their work. This study avoids such generalizations by focusing on how the use of artificially intelligent agents in scheduling shapes how managers direct their attention, which in turn shapes organizational performance and the economy at large. Understanding these processes is important because of the broad consequences that entrusting attention management to AI will have, from influencing innovation to enabling or inhibiting organizational learning by affecting the knowledge to which organizations have access. The findings of the study will shape our understanding of what work technology is equipped to do, how organizational members should be trained to work with AI, and how to mitigate unintended consequences of using AI to guide our decision making. This project investigates how decisions about time and attention are outsourced to both AI and human agents and utilizes ethnographic methods to gather rich interview and observational data from several field sites. In doing so, the study contributes to intellectual conversations in three main areas. First, the findings of this study will help revise existing theoretical work using an attention-based view of the firm to show how other people shape leaders' attention. Second, the findings will develop new theory about the relationship between time and attention. Though existing empirical evidence suggests that decisions about time affect attention allocation, the proposed comparative study will provide greater understanding of the mechanisms through which decisions about time come to bear on attention. Third, the study contributes to the larger area of artificial intelligence and the changing nature of work and organizing. Its findings will illuminate the choices that developers make in designing artificially intelligent technologies and identify the attributes of these tools that organizations should consider when deciding to implement them into their work. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.