Sensitivity Auditing

Sensitivity auditing (SAUD) extends sensitivity analysis (SA) by zooming out from the mere technical mathematical or statistical dimensions of a model— and reflecting on its implicit or explicit assumptions, interests, and values. SAUD takes models to be more than the translation of natural or human laws into lines of computer program or algorithms. Models are taken instead to reflect different visions of the world, of the nature of the problem tackled, and of the preferred end-in-sight. Sensitivity auditing is inspired by the epistemologies of post-normal science, for which uncertainty, quality, and values belong together in the use of science to tackle practical problems in society, the environment, and human health. Sensitivity auditing assumes settings where uncertainties, interests, and values are at stake in the taking of decisions based on different forms of quantification. It is explicitly participative and offers to its practitioners solid basis for both constructing and deconstructing cases at the science-policy interface.