Epistemic Rigidity and Information Dynamics

In the epistemic rigidity research artifact and its companion epistemic rigidity narrative, I examine a structural problem that arises when computational representations of reality become sufficiently authoritative that they begin influencing the conditions under which information, uncertainty, and human expression are recognized. The formal publication develops this problem through the relationship between epistemic rigidity and entropy. It argues that expansion of knowledge does not exempt a representational system from encounters with information that exceeds its existing structure. When preservation of an established representation takes precedence over revision, unresolved or unfamiliar information can increasingly be treated as noise, anomaly, or error rather than as possible evidence of limitations in the representation itself. The narrative complement examines the same architecture at human scale. It considers what happens when classification and representation become infrastructural, influencing what can be recognized, recommended, validated, or treated as coherent. Particular attention is given to the recursive relationship between machine representation and human adaptation: people can increasingly express themselves in forms that computational systems readily recognize, while those adapted expressions can subsequently contribute to the informational environment encountered by later systems. Across the two publications, epistemic humility is therefore treated not simply as an admission that a system might be wrong, but as an architectural capacity to remain revisable when reality exceeds an existing representation. The narrative distinguishes representation from existence, probability from impossibility, unfamiliarity from invalidity, and internal coherence from external truth. This gives the publications a coherent position: a representation should remain distinguishable from that which it represents. Applied to human cognition, this principle protects the possibility that uncertainty, anomaly, contradiction, and unfinished understanding may carry information without first having to conform to an established interpretive structure. The publications describe this human dimension as a right to remain epistemically unresolved while maintaining that unresolved states are not thereby established as true. The resulting position is neither a rejection of knowledge nor an argument against classification. It is an argument concerning the boundary of their authority. Intelligence may classify, predict, organize, and accumulate knowledge while remaining subject to correction by realities its existing representations did not anticipate. From this vantage, the two publications function as complementary expressions of one research question: whether increasingly capable systems of knowledge can preserve the distinction between what has been represented and what exists beyond the present limits of representation. The formal artifact approaches that question through information dynamics and entropy; the narrative complement examines its consequences for human agency, uncertainty, and participation.