We have already examined the worldwide trends for outcomes (measured as accidents, errors and events) using data available for large complex technological systems with human involvement. That analysis was a dissection of the basic available, published data on real and measured risks, for trends and inter-comparisons of outcome rates. We found and showed how all the data agreed with the learning theory when the accumulated experience is accounted for. Here, learning includes both positive and negative feedback, directly or indirectly, as a result of prior outcomes or experience gained, in both the organizational and individual contexts. Our purpose here and now is to try to introduce some predictability and insight into the risk or occurrence of these apparently random events. In seeking such a general risk prediction we adopt a fundamental theoretical approach that is and must be testable against the world’s existing data. Comparisons with outcome error data from the world’s commercial airlines, the two shuttle failures, and from nuclear plant operator transient control behaviour, show a reasonable level of accord. The results demonstrate that the risk is dynamic, and that it may be predicted using the MERE learning hypothesis and the minimum failure rate, and can be utilized for predictive risk analysis purposes.
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