title: Clarifying types of uncertainty: when are models accurate, and uncertainties small?
abstract: Professor Aven has recently noted the importance of clarifying the meaning of terms such as "scientific uncertainty" for use in risk management and policy decisions, such as when to trigger application of the precautionary principle. This comment examines some fundamental conceptual challenges for efforts to define "accurate" models and "small" input uncertainties by showing that increasing uncertainty in model inputs may reduce uncertainty in model outputs; that even correct models with "small" input uncertainties need not yield accurate or useful predictions for quantities of interest in risk management (such as the duration of an epidemic); and that accurate predictive models need not be accurate causal models.
authors: Cox Associates and University of Colorado, 503 Franklin St., Denver, CO 80218, USA. tcoxdenver@aol.com
authors: Louis Anthony Tony
authors: LA
authors: Cox
mesh_terms: D012308:Risk Management / Q000458:organization & administration*; D035501:Uncertainty