Essay Abstract
The fathers of the Scientific Revolution intentionally excluded mind from the scientific agenda: they wanted to (and did) build science based on the much more familiar, spatial, considerations, while the mind, they agreed, is of non-spatial nature. It seems that behind the attraction of "it from bit" lies a long suppressed in science but deep seated and probably scientifically fruitful desire to see something 'mental' emerge as the principal element in the structure of the Universe. Yet it would be very naïve to hope that the integration of the 'mental' into a scientific view can be accomplished in the historically familiar, incremental, manner, for example, by simply bringing "bits" into the focus. The scientific common sense suggests: to achieve such extraordinary goal requires an extraordinary scientific step, which I propose is the replacement of our numeric 'glasses' with new, non-numeric, 'glasses'. To this end, we have developed a fundamentally new--'informational', or structural--form of data representation, called "struct", intended to capture previously inaccessible view of objects and processes. It might be considered as a far-reaching generalization of the underlying idea of causal sets (in quantum gravity). The struct promises not only to serve as the blueprint for all "its", including space, but is supposed to elucidate the nature of the discovered in the last century ubiquitous discreteness. However, as never before in the history of science, the pragmatic question is this: Since it is the spatial considerations that for several millennia have fully guided the development of mathematics and physics, how many physicists are prepared to start the development of physics more or less anew, on top of such or similar informational structure (as opposed to the present 'safe' flirtations with the bits)?
Author Bio
Diploma in Mathematics (topology; St.-Petersburg University) and Ph.D. in Systems Design Engineering (pattern recognition; University of Waterloo). I worked as a professor in the Faculty of Computer Science, UNB, Canada, and served on the editorial boards of several journals. After an early retirement, I am writing a book, do research and consulting. Trained as a mathematician, I was especially influenced by Bourbaki view of mathematical structures. In my research in pattern recognition, I realized the inadequacy of the numeric formalisms, including the probabilistic models, and have been working on the development of a fundamentally new (ETS) formalism for structural representation.