A man provided with paper, pencil, and rubber, and subject to strict discipline, is in effect a universal machine. (Turing 1948: 9.)
"Turing showed that his very simple machine ... can specify the steps required for the solution of any problem that can be solved by instructions, explicitly stated rules, or procedures" (Gregory 1987: 784).
Margaret Boden argues for a connectionist view of human nature. While arguing that the human mind functions like a computer, she denies that it functions like a digital computer. Rather, she believes that the human mind is a complex computer that uses neural networks, as well as some basic procedural hardware in order to think.
Connectionism is a movement in cognitive science which hopes to explain human intellectual abilities using artificial neural networks (also known as `neural networks' or `neural nets'). Neural networks are simplified models of the brain composed of large numbers of units (the analogs of neurons) together with weights that measure the strength of connections between the units. These weights model the effects of the synapses that link one neuron to another. Experiments on models of this kind have demonstrated an ability to learn such skills as face recognition, reading, and the detection of simple grammatical structure.
Philosophers have become interested in connectionism because it promises to provide an alternative to the classical theory of the mind: the widely held view that the mind is something akin to a digital computer processing a symbolic language. Exactly how and to what extent the connectionist paradigm constitutes a challenge to classicism has been a matter of hot debate in recent years.
The last thirty years have been dominated by the classical view that (at least higher) human cognition is analogous to symbolic computation in digital computers. On the classical account, information is represented by strings of symbols, just as we represent data in computer memory or on pieces of paper. The connectionist claims, on the other hand, that information is stored nonsymbolically in the weights, or connection strengths, between the units of a neural net. The classicist believes that cognition resembles digital processing, where strings are produced in sequence according to the instructions of a (symbolic) program. The connectionist views mental processing as the dynamic and graded evolution of activity in a neural net, each unit's activation depending on the connection strengths and activity of its neighbors, according to the activation function.
The above material is from: Copyright © 1997 by James W. Garson, garson@menudo.uh.edu,“Connectionism,” Stanford Internet Encyclopedia of Philosophy, 11/17/98.
A Turing machine is the minimum device (simplistic mechanism) necessary to carry out a defineable calculation. It breaks each computation down into singular steps.
A Von Neumann machine uses stored programing, hardware, and software. Historically, previous machines were all hardwired.
Boden uses the classroom example to illustrate how neural networks function. In neural networks, multiple processes occur at the same time and interact with each other, resulting in some pathways gradually increasing in strength and tendency. This leads to the resultant decision (consistency amongst all parts).
Formalist refers to Von Neumann and Turing machines. These are very procedural in nature. Every process follows a strict order and code of rules. This is representative of deductive logic.
Connectionist systems use feedback loops, which result in tendencies for certain things to follow certain pathways. However, this is only a tendency, a probability. This is representative of inductive logic. Since neural networks allow for “surprises” some people argue that they allow for at least the illusion of freedom. According to Boden, “To compute and to understand are fundamentally similar, which is why computational psychology could give use a science of the mind.” (P. 405).