Normativity, Rationality, and Judicial Discretion

Centre for Data Futures and the Jurisprudence Journal are pleased to invite you to the Annual Jurisprudence Lecture 2026 with Professor Hannah Ginsborg, UC Berkeley.

Abstract

Many philosophers, notably Joseph Raz, have held that the notion of normativity is essentially connected to that of rationality, conceived as the capacity to recognize reasons. As Raz puts it, “[t]he normativity of all that is normative consists in the way that it is, or provides, or is otherwise related to reasons” (“Explaining Normativity” (1999), p. 67). I argue against this view by appealing to the idea of “primitive normativity”: a form of normativity associated, not with rationality, but with what Kant, in the third Critique, calls the faculty of judgment. The recognition of primitive normativity is required for grasping linguistic meaning and concepts, and hence it is a prior condition of, rather than depending on, the recognition of reasons. I go on to consider the relevance of primitive normativity to questions, often considered under the head of judicial discretion, about about how judges decide “hard cases.” I suggest that these decisions are governed by normative constraints, but that, rather than being constraints of rationality, these are constraints of the more primitive kind associated with judgment.

Summary

Professor Hannah Ginsborg’s lecture offers a compelling angle for linking foundational philosophical questions about normativity to the work of the Centre for Data Futures. Challenging the idea that normativity is grounded solely in rationality, she develops the notion of primitive normativity: a more basic form of norm-guided judgment that underpins our ability to grasp meaning and act appropriately even before explicit reasoning comes into play . This perspective speaks directly to the Centre’s mission to explore how communities can shape the digital systems that increasingly structure their lives. If normativity is rooted in shared practices of judgment, rather than only in formal rules or articulated reasons, then participatory approaches to data governance and AI design must engage with these deeper, often implicit, forms of collective sense-making. In this light, Ginsborg’s work may contribute to the framing of a key challenge for the future of AI: how to design systems that not only support individual decision-making, but also preserve and enhance the capacity of communities to negotiate, revise, and refine the values embedded in their practices over time. Her lecture thus provides a rich conceptual foundation for thinking about participatory and adaptive digital infrastructures.

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Host or Publisher The Dickson Poon School of Law