Recovering the ontological value of the universals implies recognizing a hierarchy of different natures, each one characterized by proper operations.
The AI presumption of reducing a human being to a hardware, that is, a collection of components, plus a software called “mind” (such is the so-called “functionalism”) is untenable already within the limited framework of a purely phenomenological investigation. Furthermore, the recovery of the ontological significance of the universals implies that a purely scientific description can answer the “hows” but it leaves open the “why” questions which are by no means irrelevant, but which lie beyond the scientific explanation and represent its same foundation. All this should result from the following Sections dealing with the problem of complexity.
2. The Cartesian schism and modern science
The Cartesian split, or “schism”, between res cogitans and res extensa, has been the source of an automatism in the scientific endeavor which is still matter of epistemological debate. This is shown with reference to Fig. 1. Let us call R the reality, S the agent who formulates statements about reality and M the collection of our senses as well as those extensions of our senses which are our measurement apparatuses. Within the Cartesian split, M is part of res extensa, and res cogitans S receives passively the signals coded by M. S is like the film of a fixed focus camera, recording the impressions without contributing to their build up (solid line from M to S).
At the same time of the Cartesian schism, Galilei formulated his scientific program as “not attempting” to grasp the natures but just sticking to the quantitative affections” (Galilei) that is, reducing our knowledge of the world to a limited number of connotations, provided by different measuring apparatuses, each one calibrated on a proper scale. Each connotation is then coded in a number on a suitable scale. On this epistemological line, Herbert Spencer identified science as the collection of our measuring apparatuses (Cassirer).
As a result of this attitude a key role has been attributed to an expert system, that is, to a computer equipped with an archive built by a collection of different measurements. The hope that an expert system could replace human investigators in medical diagnosis or in economic forecasting is based on the Cartesian presumption that man is reducible to a group of apparatuses M plus a computer fed by the M outputs in order to start programs based on algorithms which represent models of the world.
Within this horizon, the scientific program consists in characterizing an event by a number n of measurements via n apparatuses M. The ordered collection of the n numbers represent the state of the system as a point in n- dimensional space. Therefore, a dynamical evolution is the collection of points at different times, which makes a line in such a space. The aim of scientific discovery reduces to establish which are the n essential dimensions. These are called the “degrees of freedom” of the system under observation; based on Occam razor, we must not overcome n. Powerful elaboration methods, called “nonlinear data analysis” have been developed (Abarbanel et al.) Since in nonlinear dynamics all the different degrees of freedom are tightly entangled, it is not necessary to observe all of them; it is sufficient to sample just one in course of time and then embed the corresponding one dimensional string of temporal data into spaces of increasing dimensions, 2,3,4 etc. by suitable mathematical techniques. As one overcomes n, the data analysis provides a check of redundancy, thus blocking the further growth of the dimension number and avoiding to violate Occam criterion.
Until science had provided univocal results, it was possible, like Galileo, to believe that science was reading in the book of nature discovering the same worlds which were written in it by God. The self limitation to quantitative features endowed science with an insight unknown to philosophy. The self limitation represented a creative procedure compressing the relevant information into compact formulas or laws, and disregarding those features which were irrelevant for the further evolution. This way science seemed to assure a reliable prediction of the future, and its language seemed to eliminate the ambiguities of the ordinary language. In other words science was able to isolate what was relevant in view of the world evolution. Whence the belief that any sensible discourse had to be formulated within the rules of the scientific language, avoiding the non sense of the ordinary language. This belief, initially expressed by Wittgenstein as aphorisms, was later formalized by the Wiener Kreis as a “logical construction of the world”, based on a starting group of concepts and verifiable relations (the axioms) and on the further deduction of all their possible consequences. Any problem outside this scheme was considered irrelevant (logical atheism).
However in these recent years, the attempts of scientific description of complex systems have unveiled situations not considered in the first three centuries of science. Precisely, a correct syntactic procedure does not generally lead to unique final situation, but to a large number of alternative situations with comparable probabilities of occurrence. On the contrary, the experimental observation shows that only one of the predicted outcomes has in fact realized. This gives rise to a conflict between syntax and semantics, between truth and certitude. The initial axiom set making up the scientific model must be integrated with elements of reality not included (not deducible from) that set.
