María del Rosario Martínez-Ordaz: A Network-Based Model of Understanding: Beyond Belief, Justification, and Truth

13.11.2025 15:00

Seminar room, Centre for Medieval Studies, Institute of Philosophy, CAS, Jilská 1, Prague

Abstract
Here, I argue that scientific understanding—henceforth, understanding—is best conceived as a fundamentally relational epistemic phenomenon rather than as a variant of knowledge defined by belief, justification, and truth. Building on this claim, I introduce the "Network-based Model of Understanding" (NMU), which characterizes understanding as emerging from the structure and manipulation of relations among informational, conceptual, and theoretical elements. NMU explains how understanding can persist—even thrive—when traditional epistemic markers are absent or compromised, while clarifying their supportive role when present. By modeling understanding as a network, this approach highlights the topology and dynamics of epistemic relations that underlie explanatory and predictive success. It also reframes longstanding debates, such as those concerning the factivity condition, by shifting attention from isolated truths to system-level properties that secure epistemic robustness. Finally, NMU helps clarify how complex yet misleading networks of misinformation—such as those that simulate coherence or explanatory depth in scientific communication—can appear convincing despite lacking genuine epistemic integrity. By distinguishing between structural complexity and epistemic robustness, NMU sheds light on why some distorted representations still feel intelligible and even resemble cases of genuine understanding.

The event is partially funded by the AI: Artificial Intelligence for Science and Society programme of the AV21 Strategy.