New Laws of Practice for Learning and Error Correction

Abstract

Relevant to design, operation and safety is the determination of risk and error rates. We provide the detailed comparison of our new learning and statistical theories for system outcome data with the traditional analysis of the learning curves obtained from tests with individual human subjects. The results provide a consistent predictive basis for the learning trends emerging all the way from timescales of many years in large technological system outcomes to actions that occur in about a tenth of a second for individual human decisions. Hence, we demonstrate both the common influence of the human element and the importance of statistical reasoning and analysis.