Performance based fire safety regulation under intentional uncertainty

Abstract

Many technical variables used as inputs to fire models actually represent the output of unpredictable human decisions. Human decisions related to fire safety constitute a distinct problem for fire modelling that is not captured by epistemic or aleatory uncertainty, since it is often irreducible even with additional knowledge. Intentional (teleological) uncertainty is proposed to describe this uncertainty. Performance based codes shift fire safety decision making from political to technical domains, but there exist no technical methods for resolving intentional uncertainty. Social decisions can cope with uncertainties because society can not only set overall goals but also resolve the acceptable level of uncertainty in the model, Resolution of the uncertainties will take different forms depending on whether the human decisions are internal to the model or external. External decisions represent 'conditions' for the model, which will have to be accepted politically. Decisions with credible estimates can be internal to the model. Some decision outputs cannot be estimated but can be controlled by a regulatory process as a pre-condition to the use of the model. The existence of a functioning regulatory system capable of resolving uncertainties and keeping human decisions within the conditions of the model is a prerequisite for performance based codes.