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The awareness of the physical possibility of models of space, alternative with respect to the Euclidean one, begun to emerge towards the end of the 19-th century. At the end of the 20-th century a similar awareness emerged concerning the physical possibility of models of the laws of chance alternative with respect to the classical probabilistic models (Kolmogorov model). In geometry the mathematical construction of several non-Euclidean models of space preceded of about one century their applications in physics, which came with the theory of relativity. In physics the opposite situation took place. In fact, while the first example of non Kolmogorov probabilistic models emerged in quantum physics approximately one century ago, at the beginning of 1900, the awareness of the fact that this new mathematical formalism reflected a new mathematical model of the laws of chance had to wait until the early 1980's. In this long time interval the classical and the new probabilistic models were both used in the description and the interpretation of quantum phenomena and negatively interfered with each other because of the absence (for many decades) of a mathematical theory that clearly delimited the respective domains of application. The result of this interference was the emergence of the so-called the paradoxes of quantum theory. For several decades there have been many different attempts to solve these paradoxes giving rise to what K. Popper baptized the great quantum muddle: a debate which has been at the core of the philosophy of science for more than 50 years. However these attempts have led to contradictions between the two fundamental theories of the contemporary physical: the quantum theory and the theory of the relativity. Quantum probability identifies the reason of the emergence of non Kolmogorov models, and therefore of the so-called the paradoxes of quantum theory, in the difference between the notion of passive measurements like reading pre-existent properties (urn metaphor) and measurements consisting in reading a response to an interaction (chameleon metaphor). The non-trivial point is that one can prove that, while the urn scheme cannot lead to empirical data outside of classic probability, response based measurements can give rise to non classical statistics. The talk will include entirely classical examples of non classical statistics and potential applications to economic, sociological or biomedical phenomena.

Urns and Chameleons: two metaphors for two different types of measurements