The Effects of AI on Street-Level Bureaucracy: A Scoping Review

The use of artificial intelligence (AI) by "street-level bureaucrats" - a term coined by Michael Lipsky to explain the public servants who distribute public benefits and sanctions using professional discretion in interactions with the public - has been expanding. By adopting the structure set forth in Lipsky's 2010 book, Street Level Bureaucracy, we analyze the effects of AI on the characteristic facets of their work: discretion, working conditions, and patterns of practice. According to more than 70 works gathered from across the fields of justice, policing, education, and social work, we cover how each of these has been or will likely be affected by AI and draw out the ethical implications associated with these changes. We find that AI has mixed effects on frontline discretion - at times supporting and at times limiting it. The literature suggests changes in working conditions, specifically in the form of a shift in resource constraints (from lack of time to inadequate training), technologization of performance measures (which yield few discernible advantages over traditional assessment methods and lead to privacy concerns), and client interactions influenced by their perceptions of AI (resulting from personal and contextual factors). While there is limited literature on how most patterns of practice are affected by AI use, we find that rationing at the level of clients has, across many domains, been made more efficient by the use of these tools, while exacerbating bias, due to biased training data and human-computer interaction. From the literature, we explain the potential effects of AI on three other patterns of practice - rationing at the level of services, securing client compliance, and reconceiving work and clients.