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The latest evolutionary phase in programming is OOPS (Object Oriented Programming Systems). Objects are modules which encompass both data and instructions in self contained units. The user communicates with functions performed by these objects - but not with their structure and internal processes.
Programming objects, in other words, are "black boxes" (an engineering term). The programmer is unable to tell how object does what it does, or how does an external, useful function arise from internal, hidden functions or structures. Objects are epiphenomenal, emergent, phase transient. In short: much closer to reality as described by modern physics.
Though these black boxes communicate - it is not communication, its speed, or efficacy which determine overall efficiency of system. It is hierarchical and at same time fuzzy organization of objects which does trick. Objects are organized in classes which define their (actualized and potential) properties. The object's behaviour (what it does and what it reacts to) is defined by its membership of a class of objects.
Moreover, objects can be organized in new (sub) classes while inheriting all definitions and characteristics of original class in addition to new properties. In a way, these newly emergent classes are products while classes they are derived from are origin. This process so closely resembles natural - and especially biological - phenomena that it lends additional force to software metaphor.
Thus, classes can be used as building blocks. Their permutations define set of all soluble problems. It can be proven that Turing Machines are a private instance of a general, much stronger, class theory (a-la Principia Mathematica). The integration of hardware (computer, brain) and software (computer applications, mind) is done through "framework applications" which match two elements structurally and functionally. The equivalent in brain is sometimes called by philosophers and psychologists "a-priori categories", or "the collective unconscious".
Computers and their programming evolve. Relational databases cannot be integrated with object oriented ones, for instance. To run Java applets, a "virtual machine" needs to be embedded in operating system. These phases closely resemble development of brain-mind couplet.
When is a metaphor a good metaphor? When it teaches us something new about origin. It must possess some structural and functional resemblance. But this quantitative and observational facet is not enough. There is also a qualitative one: metaphor must be instructive, revealing, insightful, aesthetic, and parsimonious - in short, it must constitute a theory and produce falsifiable predictions. A metaphor is also subject to logical and aesthetic rules and to rigors of scientific method.
If software metaphor is correct, brain must contain following features:
Parity checks through back propagation of signals. The brain's electrochemical signals must move back (to origin) and forward, simultaneously, in order to establish a feedback parity loop. The neuron cannot be a binary (two state) machine (a quantum computer is multi-state). It must have many levels of excitation (i.e., many modes of representation of information). The threshold ("all or nothing" firing) hypothesis must be wrong. Redundancy must be built into all aspects and dimensions of brain and its activities. Redundant hardware -different centers to perform similar tasks. Redundant communications channels with same information simultaneously transferred across them. Redundant retrieval of data and redundant usage of obtained data (through working, "upper" memory). The basic concept of workings of brain must be comparison of "representational elements" to "models of world". Thus, a coherent picture is obtained which yields predictions and allows to manipulate environment effectively. Many of functions tackled by brain must be recursive. We can expect to find that we can reduce all activities of brain to computational, mechanically solvable, recursive functions. The brain can be regarded as a Turing Machine and dreams of Artificial Intelligence are likely come true. The brain must be a learning, self organizing, entity. The brain's very hardware must disassemble, reassemble, reorganize, restructure, reroute, reconnect, disconnect, and, in general, alter itself in response to data. In most man-made machines, data is external to processing unit. It enters and exits machine through designated ports but does not affect machine's structure or functioning. Not so brain. It reconfigures itself with every bit of data. One can say that a new brain is created every time a single bit of information is processed.
Only if these six cumulative requirements are met - can we say that software metaphor is useful.
Sam Vaknin is the author of Malignant Self Love - Narcissism Revisited and After the Rain - How the West Lost the East. He is a columnist for Central Europe Review, United Press International (UPI) and eBookWeb and the editor of mental health and Central East Europe categories in The Open Directory, Suite101 and searcheurope.com.
Visit Sam's Web site at http://samvak.tripod.com