Absolute Probability Judgement

Absolute probability judgement is a technique used in the field of human reliability assessment (HRA), for the purposes of evaluating the probability of a human error occurring throughout the completion of a specific task. From such analyses measures can then be taken to reduce the likelihood of errors occurring within a system and therefore lead to an improvement in the overall levels of safety. There exist three primary reasons for conducting an HRA; error identification, error quantification and error reduction. As there exist a number of techniques used for such purposes, they can be split into one of two classifications; first generation techniques and second generation techniques. First generation techniques work on the basis of the simple dichotomy of ‘fits/doesn’t fit’ in the matching of the error situation in context with related error identification and quantification and second generation techniques are more theory based in their assessment and quantification of errors. ‘HRA techniques have been utilised in a range of industries including healthcare, engineering, nuclear, transportation and business sector; each technique has varying uses within different disciplines.

Absolute probability judgement, which is also known as direct numerical estimation, is based on the quantification of human error probabilities (HEPs). It is grounded on the premise that people cannot recall or are unable to estimate with certainty, the probability of a given event occurring. Expert judgement is typically desirable for utilisation in the technique when there is little or no data with which to calculate HEPs, or when the data is unsuitable or difficult to understand. In theory, qualitative knowledge built through the experts’ experience can be translated into quantitative data such as HEPs.

Required of the experts is a good level of both substantive experience (i.e. the expert must have a suitable level of knowledge of the problem domain) and normative experience (i.e. it must be possible for the expert, perhaps with the aid of a facilitator, to translate this knowledge explicitly into probabilities). If experts possess the required substantive knowledge but lack knowledge which is normative in nature, the experts may be trained or assisted in ensuring that the knowledge and expertise requiring to be captured is translated into the correct probabilities i.e. to ensure that it is an accurate representation of the experts’ judgements.