Knowledge involves selecting information from the outside world and orienting one's behaviour based on both past experiences and new situations, creating the conditions for studying complex adaptive systems and the emerging phenomena associated with them. The complexity of a system, therefore, is a property of the currently available scientific representation of the system model, consisting of the observer who constructs the model and the model itself. However, complexity does not only include the quantity of units and interactions, but also uncertainties, indeterminacies, and random phenomena. These considerations should put an end to the endless pseudo-philosophical discussions on the relationship between mind and computer, sparked by developments in “Artificial Intelligence”. The fundamental goals of research in the field of Artificial Intelligence are not so much to build systems that ‘imitate’ humans exactly, but rather to build systems that are “better” than current computers. In other words, what matters most is to have artificial systems that are “useful” to us, with which we can interact “naturally”, enabling computers to simulate complex “reasoning” and other cognitive activities that have until now been exclusive to natural intelligence.
Giovanni Maria Guazzo (Sat,) studied this question.
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