Datzov, Nikola, AI Jurisprudence: Toward Automated Justice (September 9, 2024 – Revised December 4, 2025). Available at SSRN: https://ssrn.com/abstract=5178780  “The U.S. judiciary’s evolving role and digitization into a “modern” court system over the past several decades has brought it to a fundamentally altering moment: the adoption of automated justice. Recent developments in artificial intelligence (AI) have presented unprecedented capabilities for legal writing, legal analysis, and legal decision-making to be performed by automated technologies. The “AI Revolution,” among other things, has led to the first adoptions of automated adjudicators and judicial “employees” in numerous courts around the world. While the rest of the world has been grappling with the complex questions relating to AI’s arrival at the courthouse steps, surprisingly, courts in the United States have largely ignored their inevitable future until very recently. This unfortunate oversight has left the use of AI technology in judicial decision-making at the hands of individual judges—many of whom lack a sound understanding of the technology—without any formal guidance on its capabilities, limits, and risks. This article is one of the first to closely examine several important concepts at the heart of U.S. courts’ path toward automated justice and comprehensively connect interdisciplinary scholarship from several diverse areas of law in the context of modern AI and judicial decision-making. Thus, it offers several significant contributions so far absent from existing literature regarding how the fundamental concept of justice will be preserved in U.S. courts in light of the AI Revolution. The article first tells the overlooked story of the courts’ unwitting transition toward an AI-ready judiciary and provides a descriptive account of the evolving capabilities of AI to perform judicial work. To help frame and structure future discussions of AI’s role in performing such judicial functions, the article introduces a novel taxonomy that categorizes the work of judges into different AI tiers and levels, namely AI-Assisted, AI-Led, and AI-Automated Judges. Such a taxonomy is critical because a more granular approach is necessary to determine the metes and bounds of where AI can replace certain judicial responsibilities for certain types of cases. It also examines whether any barriers exist to incorporating AI into the judiciary, including the constitutionality of delegating judicial work to modern AI, which to date has not been meaningfully considered in existing literature. Additionally, the article tackles the complex normative questions surrounding automated judicial decision-making (at different levels) through the lens of historical legal theory and further divides appropriate AI justiciability into the proposed taxonomy. Finally, it explores the complicated question of who can tell judges how to use AI in their judicial work and advocates for a desperately needed judge-led framework of “guided discretion” to transition U.S. courts into the age of AI based on seven fundamental principles.”