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     In recent years, computer science, as well as cognitive science and neuroscience have presented strong refutations to classical models of intelligence. Most of the standard cognitive models are based upon introspection and subjective perception of the computational process of cognition. This typically leads to the assumptive bias that intelligence is based upon a monolithic general processing control system. Though there is a substantial volume of theory attempting to address the obvious flaws in such a model. An example being arbitrary representation of the conscious and unconscious minds as two discrete cognitive entities, or more significantly Freud's multiple entity representation. This tendency is not limited to behavioral sciences, as obviated in computer science by Marvin Minsky's "Society Of Mind" (1986).

     The author's assertion is that these representations are variations on the same theme of "general purpose" islands of awareness and computation. In recognition of the incongruity between the perceptual monolithic "I" of self-experienced intelligence and the ever increasing volume of data refuting this, the solution has been to propose multiple "I" models with elaborate voting or dominance control structures. The substance of the assertion being that all models are based upon generalized non-modal processing of sub-units whose very existence is theorized from the perceptual and arbitrary granularity of the theorist's personal introspection, as well as biases towards computational metaphors (such as mathematical logic and linear reasoning). This would explain why the proposed number and type of sub-units is based upon classification of human drives, urges, and tendencies. Though this might be a logical assumption it is not necessarily remotely representative of the actual cognitive and neurological processes.

     Simple introspection and biased observation can lead one to believe in a neurological equivalent of the central processing unit, something that makes the decisions and controls the other functions of the organism. While there are undoubtedly control structures, this model of a single, unitary control system is not supported by evidence from cognitive science. One example comes from studies of split brain patients by Gazzaniga and LeDoux. As an experimental treatment for severe epilepsy in these patients, the corpus callosum (the main structure connecting the two hemispheres of the brain) was surgically cut. The patients are surprisingly normal after the operation, but with deficits that are revealed by presenting different information to either side of the (now unconnected) brain. Since each hemisphere controls one side of the body, the experimenters can probe the behavior of each hemisphere independently (for example, by observing the subject picking up an object appropriate to the scene that they had viewed). In one example, a snow scene was presented to the right hemisphere and the leg of a chicken to the left. The subject selected a chicken head to match the chicken leg, explaining with the verbally dominant left hemisphere that "I saw the claw and picked the chicken". When the right hemisphere then picked a shovel to correctly match the snow, the left hemisphere explained that you need a shovel to "clean out the chicken shed" (from p. 148 of Gazzaniga and LeDoux). The separate halves of the subject independently acted appropriately, but one side falsely explained the choice of the other. This suggests that there are multiple independent control systems, rather than a single monolithic one, and that the division between these systems is not based upon classical definitions.

     The brain is conventionally thought to be a general purpose machine, acting with equal skill on any type of operation that it performs by invoking a set of powerful rules. However, humans seem to be proficient only in particular sets of skills, at the expense of other skills, often in non-obvious ways. A good example of this is the Stroop effect. When presented with a list of words written in a variety of colors, performance in a color recognition and articulation task is dependent on the semantic content of the words; the task is very difficult if names of colors are printed in non-corresponding colors. This experiment demonstrates the specialized nature of human computational processes and interactions. Even in the areas of deductive logic, humans often perform extremely poorly in different contexts. Wason (1966) found that subjects were unable to apply the negative rule of if-then inference when four cards were labeled with single letters and digits. However, with additional context---labeling the cards such that they were understandable as names and ages---subjects could easily solve exactly the same problem. Further, humans often do not use subroutine-like rules for making decisions.

     The work of Gazzaniga and LeDoux seems to indicate that the perceptual "I" of cognition is a function of explaining (or rationalizing) the behavior of the underlying control systems. The Stroop effect seems to indicate underlying modal processing by specialized control systems. There is significant evidence of this in neuroscience as indicated by studies in regional brain activity during experiments designed to isolate visual, auditory, and tactile responses. Humans have the capability to receive an enormous amount of information from the world. Visual, auditory, tactile, and olfactory cues are all processed simultaneously to provide us with our view of the world. However, there is evidence that the sensory modalities are not independent; stimuli from one modality can and do influence the perception of stimuli in another modality. For example, Churchland, Ramachandran, and Sejnowski (1994) demonstrated an example of how audition can cause illusory visual motion. Vision can cause auditory illusions too, such as the McGurk effect. These studies demonstrate that sensory modalities cannot be treated independently, as well as the subjective interpretation of our environment.

     There is evidence that in normal tasks humans tend to minimize their internal representation of the world. Ballard, Hayhoe, and Pelz (1995) have shown that in performing a complex task, like building a copy of a display of blocks, humans do not build an internal model of the entire visible scene. By changing the display while subjects were looking away, Ballard found that subjects noticed only the most drastic of changes; rather than keeping a complete model of the scene, they instead left that information in the world and continued to refer back to the scene while performing the copying task. There is also evidence that there are multiple internal representations, which are not mutually consistent. For example, in the phenomena of blindsight, cortically blind patients can discriminate different visual stimuli, but report seeing nothing. This inconsistency would not be a feature of a single central model of visual space. These experiments and many others like it, such as the work by Gazzaniga and LeDoux on split brain patients or Rensink, O'Regan, and Clark on changes in visual scenes, convincingly demonstrate that humans do not construct a full, monolithic model of the environment. Instead humans tend to only represent what is immediately relevant from the environment, and those representations do not have full access to one another.

     These factors seem to indicate that the underlying cognitive structures of the human mind correlate with the physical sensory mechanisms of the body, rather than the logical hierarchical models we typically apply. Further, the subjective experience of "I" seems to be a function of interpreting the computational results of specialized modal processing. One tentative proposal would be the possibility that the illusion of singular thought is created by a dedicated system of interpretation of all modal systems, much like the visual processing system generalizes visual input and does not maintain a full internal representation of the environment. The proposed "I" mechanism could therefore function in similar fashion by not truly maintaining a full representation of the thought process, but filling in the gaps to create an illusion of linear process.

     Though the propositions herein do not justify supplanting standard psychological models and methodology, the author would assert that understanding of actual cognitive structure and behavior would greatly improve effectiveness of statistical and biased modeling of the human mind.