Human Errors as an Invaluable Source for Experienced Decision Making

In this paper the traditional paradigm for learning and training of operators in complex systems is discussed and criticised. There is a strong influence (the doctrine of 'mental logic') coming from research carried out in artificial intelligence. The most well known arguments against the artificial intelligence approach are presented and discussed in relation to expertise, intuition and implicit knowledge. The importance of faults and errors are discussed to describe expertise, and how knowledge about unsuccessful behaviour influences the actual decision making process of experts