Human actions and errors in risk handling—an empirically grounded discussion of cognitive action-regulation levels

Knowledge and error flow from the same mental sources, only success can tell the one from the other (Mach, E., 1905. Knowledge and Error. Sketches on the Psychology of Enquiry. D. Reidel Publishing Company, Dordrecht (translated into English, 1976). The current paper is concerned with human actions and errors that have accidents with an injury outcome as their consequence. Its aims are to identify and describe the occurrence of risk-triggering and risk-creating human errors, and to analyze the cognitive regulation levels of risk-triggering actions. This provides a basis on which to discuss some difficulties involved in the assigning of regulation levels to actions. The empirical material employed in the paper consists of data from 76 in-depth investigations of accidents in automated production. Risk-creating errors were found in 93% of cases, and were made at various organizational levels in the companies. The amount of and character of the risk-creating errors point to the importance of interventions that promote learning at the levels of the work team and the organization. In 88% of cases there was also a human error that triggered the risk. Risk-triggering errors were made at all cognitive-regulation levels. The conclusions concern methodological issues and theoretical question marks arising. There emerged a need to distinguish between the outcome of an action and its further consequences. Classification of regulation levels involved in human error was found to be fraught with difficulties when drawing boundaries between levels. Actions at different levels appeared to intervene and take over from each other, leaving errors at category interfaces. The structural aspect of action as a composite phenomenon might mean that it is not always possible to assign any particular act to a specific level, and since a task or an action usually is composed of several behavioral components the action could be assigned to several levels simultaneously. This raises questions concerning the applicability of the Skill–Rule–Knowledge (SRK) model to triggering errors in automated production. [Copyright &y& Elsevier]