Concepts, proto-concepts, and shades of reasoning in neural networks

One of the most important functions of concepts is that of producing classifications; and since there are at least two different types of such things, we better give a preliminary short description of them both. The first kind of classification is based on the existence of a property common to all the things that fall under a concept. The second, instead, relies on similarities between the objects belonging to a certain class A and certain elements of a subclass AS of A, the so-called ‘stereotypes.’ In what follows, we are going to call ‘proto-concepts’ all those concepts whose power of classification depends on stereotypes, leaving the term ‘concepts’ for all the others. The main aim of this article is showing that, if a proto-concept is given simply in terms of the ability to make the appropriate distinctions, then there are stimulus-response cognitive systems — whose way of manipulating information is based on Neural Networks (NN) — able to make the appropriate distinctions typical of proto-concepts in the absence of high-level cognitive features such as consciousness, understanding, representation, and intentionality. This, of course, implies that either proto-concepts cannot be given simply in terms of the ability to make the appropriate distinctions, or that we need to modify our traditional conception of mind, because the induction-like procedure followed by a NN in producing its classifications, far from being the ultimate product of a ‘linguistic mind,’ is, rather, inscribed in the nuts and bolts of the system’s biology/electronics to which the NN belongs.