Résumé : Electrochemical interfaces are often described through scalar, averaged observables, yet the processes that generate these are local, heterogeneous, and dynamic. As local and single-entity electrochemical methods approach the scale of individual events, apparent experimental variability becomes a source of mechanistic information. A central challenge is determining whether observed variability arises from intrinsic stochasticity, unresolved structural heterogeneity, or the measurement itself. This review examines recent examples from local electrochemistry through this lens of uncertainty and variability. We argue that local responses are better understood as distributions rather than isolated traces, and that apparent stochasticity or determinism depends not only on interfacial physics, but also on how processes are driven, sampled, and resolved. We discuss how data-rich measurements, probabilistic models, clustering approaches, and correlative readouts can separate temporal fluctuations from spatial heterogeneity and distinguish meaningful interfacial variability from instrumental artifacts. This perspective can help transform local electrochemistry from descriptive into mechanistically rigorous and predictive