Street-Level Bureaucrats & AI Interactions in Public Organizations: An Identity Based Framework

Today, various types of artificial intelligence (AI) are emerging as potential information and communication technologies (ICTs) to be integrated into the workplace. Recent work focuses on the potential impacts of AI on public service delivery (Battaglini et al., Citation2022; Meijer & Wessels, Citation2019) and bureaucratic decision-making (Bullock, Citation2019; Young et al., Citation2019). Yet little is understood regarding public employees-generative AI interactions and how these interactions affect work outcomes. Street-level bureaucrats make decisions with considerable discretion, while they interact with the public (Lipsky, Citation1980). While AI can be utilized as a tool by street-level bureaucrats, it also may eliminate human roles and stand in as an "artificial bureaucrat" (Bullock & Kim, Citation2020). The integration of generative AI may shape employees' role identities, which in turn affect their psychosocial outcomes. We develop a theoretical framework that investigates how human-generative- AI interactions affect street-level bureaucrats' work outcomes. The framework focuses on two main components: (1) the extent to which generative AI takes part at work; and (2) how human-generative AI interactions shape street-level bureaucrats role identity and their psychosocial outcomes. We integrate literature about workplace identity and job demands-resources theory to provide a set of propositions that can be applied in public organizations.