Troy, N.Y. — The latest edition of the Oxford English Dictionary boasts 22,000 pages of definitions. While that may seem far from succinct, new research suggests the reference manual is meticulously organized to be as concise as possible — a format that mirrors the way our brains make sense of and categorize the countless words in our vast vocabulary.

“Dictionaries have often been thought of as a frustratingly tangled web of words where the definition of word A refers users to word B, which is defined using word C, which ends up referring users back to word A,” said Mark Changizi, assistant professor of cognitive science at Rensselaer Polytechnic Institute . “But this research suggests that all words are grounded in a small set of atomic words — and it’s likely that the dictionary ’s large-scale organization has been driven over time by the way humans mentally systematize words and their meanings.”

Dictionaries are built like an inverted pyramid. The most complex words (e.g., “albacore” and “antelope”) sit at the top and are defined by words that are more basic, and thus lower on the pyramid. Eventually all words are linked to a small number of words — called “atomic words,” such as “act” and “group”) — that are so fundamental they cannot be defined by simpler terms. The number of levels of definition it takes to get from a word to an atomic word is called the “hierarchical level” of the word. Changizi’s research, which was published online this week and will appear in the June print edition of the Journal of Cognitive Systems Research, indicates that the dictionaries we use every day utilize approximately the optimal number of hierarchical levels — and provide a visual roadmap of how the lexicon itself has culturally evolved over tens of thousands of years to help lower the overall “brain space” required to encode it, according to Changizi.

Many other human inventions — such as writing and other human visual signs — have been designed either explicitly or via cultural selection over time so as to minimize their demands on the brain, Changizi said. By conducting a series of calculations based on the estimation that the most complex words in the dictionary total around 100,000 different terms, and that the number of atomic words range from 10 to 60, Changizi was able to devise three signature features present in the most efficient dictionaries — as well as in their human counterpart, the brain. Most importantly, he discovered that the total number of words across all the definitions in the dictionary (and thus the size of the dictionary) changes in relation to the total number of hierarchical levels present. Optimal dictionaries should have approximately seven hierarchical levels, according to Changizi.

“The presence of around seven levels of definition will reduce the overall size of the dictionary, so that it is about 30 percent of the size it would be if there were only two hierarchical levels,” Changizi said. Additionally, users will find that there are progressively more words at each successive hierarchical level, and that each hierarchical level contributes mostly to the definitions of the words just one level above their own, according to Changizi, who put his three predictions to the test by studying actual dictionaries.

The Oxford English Dictionary and WordNet — a large, online lexical database of English, developed at Princeton University — were found to possess all three signatures of an economically organized dictionary, and thus were organized in such a way as to economize the amount of dictionary space required to define the lexicon, according to Changizi. “Somehow, over centuries, these revered reference books have achieved near-optimal organization,” Changizi said. “That optimality can likely be attributed to the fact that cultural selection pressures over time have shaped the organization of our lexicon so as to require as little mental space and energy as possible.”

Changizi believes his research has potential applications in the study of childhood learning, where scientists could analyze how students learn vocabulary words and possibly develop ways to optimize that learning process.

Rather than simply continue in rote fashion doling out the theory of personhood (the ACE model), I’ll be using the discourse between Professor John Searle and Stevan Harnad to generally comment on philosophical and scientific inquiry.

Professor Searle is Professor of Philosophy at the University of California, Berkeley and Professor Harnad is Professor of Cognitive Science at Southampton University. They’re each highly esteemed and widely published and from the tone of their discourse, each is well skilled in the art of rhetoric. But while it may appear that they fundamentally disagree about when we might understand what ‘feelings’ are, a more insightful reading tends to reveal the REFUSAL by each to genuinely consider the other’s conceptualizations. It’s much easier to take a position and statically maintain such in the face of an opposing force than it is to stop once one is being so moved. Additionally, it takes energy to return to one’s starting point once one has been so moved. Note though that this what one is trained to do both as a philosopher and a scientist.

Why does it seem that using the computer is only getting more difficult and time consuming? The standard answer one receives from the ‘experts’ is that computer-based application complexity is directly related to the growth in the scope of the potential implementations. In essence, the more you can do with a computer, the more complicated it is to program and use. End of story.

Or is it??

It’s true that increasing system complexity is outstripping the development of processes for monitoring, diagnosing and repairing such systems. The proliferation of viruses, spyware and unwanted advertising are symptoms of just such failures. Accordingly, IBM has adopted an R&D manifesto calling for the development of ‘Autonomic Computing Systems.’ By incorporating a model of the human autonomic nervous system, IBM is betting that they can design computer systems that protect against threats, and further act to ‘heal’ damaged code. As defined by IBM, an autonomic computing system needs to “know itself” - its components must possess a system identity.

IBM is well down the road with regard to the research and development of computer systems that provide some measure of self-management. What does that mean to the computer user working to understand and use a blog, an RSS reader, technorati, delicious, or some other computer tech du jour? Nothing. IBM’s focus in this case is on the computer, not the computer user. IBM is incorporating a biological model to help ensure the survival of complex computing systems. Note, however, that IBM will attempt to frame the development of such systems as being user-centric; likely by leveraging the concepts of ‘reliability,’ ’stability,’ ‘ dependability,’ etc.

Suppose for a moment that instead of focusing on developing computers that can sense threat, self-protect and self-heal, one set out to develop computing systems that co-operate with the user. A model of the human autonomic nervous system may prove useful with regard to the control of a computing system’s impulsive fight-or-flight responses, but when such ‘involuntary’ impulses produce cooperative behavior, the feeling is disingenuous at best. More likely, such a form of cooperation will be perceived by the user as outright condescension. One must look at a different model upon which computing systems may be designed and implemented if one is to enable human-computer cooperation.

The conceptualization of such a model first requires the consideration of an axiom of technological development distinct from the popular idea that technology is developed to maximize the likelihood of survival. If such is the case then technological development is the cognitive recapitulation of biological evolution.

The Survivalist Model

The first technologies people invented included control over fire and the fashioning of weapons. Fire to provide heat and light, weapons to provide a means of protection and a means for obtaining protein rich food. Of course, some might argue that weapons today aren’t developed to maximize the likelihood of survival. When considered from the point of view of an individual or a nation, however, it can be argued that even the development of the atom bomb was initiated with an eye toward survival.

Arguments Against the ‘Survivalist Model’

Given the second law of thermodynamics, systems tend towards minimum energy and maximum entropy. As demonstrated by Brillouin, entropy in a system is not decreased merely because an agent within the system adds order. By adding order, the agent in fact adds entropy exceeding the amount of order so added. Therefore, it seems absurdist that the ‘goal’ of ‘life,’ is simply survival. Survival is not the end. Additionally, the emergence of cognitive systems such as those exhibited by humans would not preclude the homogenization of information and the concomitant increase in entropy and the decrease in energy. Note also, that given the success evolution has displayed over the millennia, and given the prevalence of human-on-human intolerance and violence, one might just as easily argue that cognition better represents the possible end of the human species rather than its continued survival.

The Self-Discovery Model

An alternative perspective founds the development of technology not simply upon survival, but rather upon the will to maximize the potential for self-discovery. Such a foundation subsumes the survival model, as one’s survival is necessary for a continued process of self-discovery. Note, however, that while there exist belief systems based upon the concept of reincarnation, such does not negate the idea that technology is in fact purposed to serve self-discovery rather than survival.

Two concepts relating to the Self-Discovery model that one ought consider then are ‘direct social benefit’ and ‘technology overhead.’ Direct social benefits are those measurable opportunities for self discovery introduced, or promoted by a given technology. Technology overhead is the measurable cost relating to the implementation of a technology. Whenever a person must consciously act to operate a piece of technology, such as when learning to drive a car, the user becomes an extension of the technology, if only as a means to understand it. For most all technologies, the direct social benefit conferred upon the user far outstrips the proportionately small amount of time spent learning to utilize the technology. Think riding a bicycle, driving a car, reading, writing, etc. The social benefit additionally outweighs the risks associated with injury, or loss of life while employing a technology. Once learned, driving requires very little in the way of one’s conscious attention and one is free to place one’s attention on other things.

It seems that there is only one technology that violates the Self-Discovery Model of technological development, the computer. People are required to spend more and more time learning both how to program and use the computer, rather than simply working with the computer as an additional vehicle for self-discovery. Even as models become more abstract, computing systems become more complex. Whereas abstraction ought to lead to a simplification (the loss of distinctions and cognitive overhead), one finds just the opposite is true with regard to computers. It appears that humanity has considered the computer as simply just another tool to aid survival, when in fact it is to serve as a partner for self-discovery. Therefore, one needs to imbue in a computer more than just a will to survive. The computer must include the ability to discover an increasingly distinguishable sense of identity.

The introduction of such a system represents a turning point in the cognitive evolution of humanity. Computers will manage lower level abstractions that today extract a near intolerable payment in terms of conscious attention. People will be able to refocus on higher abstractions that demonstrate interconnectedness rather than distinction while cooperating with and learning alongside computers.

–If you agree, or if you disagree, please comment and share your thoughts with others…