Assessing Confidence in Performance Assessments Using an Evidence Support Logic Methodology: An Application of Tesla

The assessment of uncertainties and their implications is a key requirement when undertaking performance assessment (PA) of radioactive waste facilities. Decisions based on the outcome of such assessments become translated into judgments about confidence in the information they provide. This confidence, in turn, depends on uncertainties in the underlying evidence. Even if there is a large amount of information supporting an assessment, it may be only partially relevant, incomplete or less than completely reliable. In order to develop a measure of confidence in the outcome, sources of uncertainty need to be identified and adequately addressed in the development of the PA, or in any overarching strategic decision-making processes. This paper describes a trial application of the technique of Evidence Support Logic (ESL), which has been designed for application in support of 'high stakes' decisions, where important aspects of system performance are subject to uncertainty. The aims of ESL are to identify the amount of uncertainty or conflict associated with evidence relating to a particular decision, and to guide understanding of how evidence combines to support confidence in judgments. Elicitation techniques are used to enable participants in the process to develop a logical hypothesis model that best represents the relationships between different sources of evidence to the proposition under examination. The aim is to identify key areas of subjectivity and other sources of potential bias in the use of evidence (whether for or against the proposition) to support judgments of confidence. Propagation algorithms are used to investigate the overall implications of the logic according to the strength of the underlying evidence and associated uncertainties. (authors)