varjestuses

Varjestuses is a term used in cognitive science and philosophy to describe a class of perceptual distortions that occur when individuals interpret uncertain data through the lens of a preferred explanatory model, especially an algorithmic or statistical one. The phenomenon involves the consolidation of model-based reasoning into intuitive understanding, often masking discrepancies between model outputs and the real world. In practice, varjestuses can lead to overconfidence in incorrect conclusions or underappreciation of uncertainty.

Origins: The term was articulated in theoretical discussions in the early 2020s by researchers examining the interface between human judgment and machine predictions. It is often discussed as a cautionary concept in data literacy and risk communication. The term is not tied to a single dataset or domain, but to a general pattern across contexts.

Characteristics: Varjestuses typically feature (1) reliance on a model's narrative as a proxy for reality, (2) reinterpretation of noisy data to fit the model, and (3) a feedback loop where expectations shape perception and then data appear to confirm those expectations. They frequently appear in fields that blend analytics with human judgment, such as finance, healthcare, and policy.

Implications: Recognizing varjestuses can improve transparency, encourage explicit uncertainty communication, and promote methodological pluralism.

See also: cognitive bias, confirmation bias, interpretability, epistemic humility.