Human‐Centered Governance: Reconstituting Cognitive Sovereignty in the Age of Algorithmic Systems

Contemporary intelligent systems increasingly participate in shaping, rather than merely supporting, human decision-making processes. While these systems enhance efficiency and predictive performance, they also introduce a critical but underexamined challenge: decisions may remain technically valid while becoming difficult for human actors to interpret and internalize. This misalignment is conceptualized in this study as the meaning gap, defined as the divergence between system output and human interpretive understanding.This paper proposes a human-centered governance framework that positions cognitive sovereignty—the capacity of individuals and institutions to interpret, contextualize, and assume responsibility for decisions—as a necessary condition for sustainable sociotechnical systems. The framework is structured around ten interdependent principles that collectively redefine governance as a cognitive architecture embedded within system design.Drawing on interdisciplinary literature in human–AI interaction, interpretability, and decision science, the study introduces latency as a conceptual construct describing temporal misalignment between system output and human interpretive readiness. This construct provides an integrative lens for understanding phenomena such as delayed comprehension, reduced accountability, and unstable trust in algorithmically mediated environments.Rather than treating interpretability as an auxiliary feature, the proposed framework positions it as a core system function. The paper further outlines potential pathways for operationalizing the meaning gap through measurable indicators, including time-to-comprehension, decision override frequency, and confidence misalignment.While existing frameworks have called for interpretability, few have proposed measurable indicators of cognitive alignment. This paper contributes preliminary metrics—time-to-comprehension, decision override frequency, and confidence misalignment—that operationalize the meaning gap for empirical testing.