ABSTRACT
An ordinary shipping professional has various questions about buzzwords such as digitalization, block chain, artificial intelligence and so on. Neo-shipping economicus is expected to be knowledgeable enough to adapt to the age of artificial intelligence or, in other words, computational intelligence. Artificial intelligence and computer intelligence broadly refer to the same concept. Machine learning, artificial neural networks and its complex variant, deep learning, fall into the area of computational intelligence. One of the biggest uses of machine learning is predictive analytics. There are various reasons behind the failure of machine learning in shipping market prediction. The naive forecaster test is a powerful instrument to spot a predictive liar of any kind. As a fundamental rule, curve-fitting has very limited value in terms of predictive accuracy, regardless of the methodology used to fit the curve. In forecasting research, there are so many methodologies that stretch out econometrics to digital signal processing and other fractions of computational intelligence.
