Contemporary AI governance frameworks focus predominantly on identifiable risks arising from model outputs, system capabilities, or post-hoc harms. This paper identifies a distinct and upstream failure mode: governance breakdown occurring prior to identifiable risk, at the level of AI-mediated judgment formation. When probabilistic language systems participate in shaping human interpretation, confidence, framing, and relevance—without being recognised as a causal substrate—risk is displaced rather than detected. This paper situates this failure within established scientific and sociotechnical literature, demonstrating that the phenomenon is neither speculative nor ethical, but a structural misclassification arising from the interaction between human judgment, institutional procedures, and AI-mediated language systems.
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Victoria Gavaza
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Victoria Gavaza (Wed,) studied this question.
www.synapsesocial.com/papers/698586238f7c464f2300a1bf — DOI: https://doi.org/10.5281/zenodo.18488910