As we have seen in Section 3.1, there is some evidence of a limitation in the rate of processing information. George Miller has compiled this evidence in his article The magical number seven, plus or minus two: some limits on our capacity for processing information [MILLER]. However, there is no evidence that anyone has reached the limit to the memory capacity of the human brain. The argument that senility is nature's way of saying "disk full" is vitiated by the fact that it is the creative people (whose brains are fuller) who are most resistant to senility.

It may well be that the problem of information overload is a pseudo-problem; yet another illustration of our human capacity to turn solutions into problems. One consistent finding in years of research on intelligence is that intelligence is a function of the richness of the environment of the organism. Smart people grow up in enriched environments and stupid people in impoverished environment. The traditional outside-in teaching was appropriate in impoverished environments, where the tell-'em-and- test-'em sessions with a teacher provided at least some enrichment. However, we now have incredibly rich environments which can help pull out the human potential. We turn this solution of a rich environment into a problem of information overload. A magnificent smorgasbord of food is a problem only if you think you must eat it all. Perhaps, people raised within an outside-in educational system tend to think that they must assimilate everything in that rich smorgasbord of information in our modern environment. The inside-out teacher - whose concept of the person is of someone growing from the inside out rather than being conditioned from the outside in - welcomes the richness.

The information overload problem may perhaps best be rephrased as one of the management of complexity.¹⁰¹ Our information-rich modern environment permits us to build complex, subtle subjective maps of the objective world. The challenge is to organize the diverse information pouring in from the wide variety of sources into a coherent and comprehensive subjective map. It is not a quantitative matter of too much content but rather a qualitative matter of putting content into context. We must learn how to put data into context to yield information, information into context to yield knowledge, knowledge into context to yield understanding, and understanding into context to yield wisdom, as we move up that data-wisdom hierarchy, which was described above as the means of adding value to the raw material of the information society.

For most people complexity is not a problem. They deal with it by simply refusing to assimilate any information which does not fit within whatever subjective map of the objective world they have settled for as satisfactory. The Jehovah Witness looks around nonplused at all my books. He has one book which contains all the answers. The retiree (in body and in mind) has no need to learn anything more. He will devote his last few years to hitting a ball into a hole with a stick. The 'philosopher' in the local pub learns nothing because he already knows everything. His wife has returned the encyclopedia. The specialist in the university sacrifices breadth at the altar of depth. Complexity can perhaps be contained within a narrow domain. Much of the popularity of Ronald Reagan may be due to the fact that he was, not so much the Great Communicator as the Great Simplifier. Berelson and Steiner, in compiling an inventory of scientific findings about human behavior concluded that the human being is a "creature who adapts reality to his own ends, who transforms reality into congenial form, who makes his own reality" [BERELSON & STEINER].

For those of us who still regard it as a problem, one constructive response to the challenge is to develop skills for managing complexity. Those skills go beyond the traditional information-processing skills of speaking and listening, reading and writing. We can add to the explaining skills of speaking and writing the skills which I will call heuristics (the set of skills for organizing information at the source for effective transmission), and we can add to the traditional understanding skills of listening and reading the skills which I will call mnemonics (the set of skills for organizing information at the destination for effective reception) (Figure 10-1).

We have already looked at a number of tools for the management of complexity. The Triad Model (see Figure 3-2) helped organized vast amounts of information within an optimal seven categories. The Four Generations of Media model (see Figure 1-3) helps organize information within the technosphere, once again within an optimal seven categories, and serves as a structure for this book. The siliclone (see Figure 8-5) is a device for removing the clutter of content, which is often mistaken for complexity. Idea processors and authoring languages (see Figure 8-2) help us organize information in two dimensions of hierarchical structures and three dimensions of networks of interlinked nodes.

Some of the many recent books on this issue - e.g. Alvin Toffler's warning about Future Shock [TOFFLER 1971] and David Shenk's warning about Data Smog [SHENK] - are phrased in terms of information overload, and some - e.g. Kevin Kelly's warning about being Out of Control [KELLY] and Thomas Homer-Dixon's warning about being faced with The Ingenuity Gap [HOMER-DIXON] - are phrased in terms of the management of complexity. Read those books to get a grasp of the problem.

All I am adding here is the argument that complexity has always been a feature of the objective world - what is new is the recognition that it must therefore become a feature of our subjective maps. Complexity was here in the ecosphere before we arrived. We have added to that complexity in the sociosphere and the technosphere and the super-complexity of the interactions among those three great spheres, and we have been arrogantly assuming that we can manage this complexity by extrapolations from our various "toys" in the technosphere. What is new is the recent recognition that we must turn from the mechanism to the organism as our model, from physics to biology as our basic discipline, from simple to complex systems as our focus. This is not rocket science. Rocket science is easy.

Media no doubt contributes to this complexity. However, it can also contribute to the management of complexity. The Big Story of the co-evolution of the person and media told here could be considered as the story of how our species extended our nervous systems to manage the increasing complexity as we moved from a hunter-gatherer to an agricultural to an industrial and now to an information society.

The Toronto School of Media Studies falls within the intelligence amplification (IA) tradition of the history of computing. This whole IA tradition, documented brilliantly by Howard Rheingold, could be considered as the story of the management of complexity [RHEINGOLD 1985]. Just as the microscope makes the too-small large enough to study, and the telescope brings the too-far near enough to study; the computer makes the too-complex simple enough to study. Thierry Bardini documents the life of Douglas Englebart which has been devoted to the management of complexity [BARDINI]. His strategy is not the traditional one of simulating the organism with a mechanism - artificial intelligence (AI), but the alternative strategy of supplementing the organism with a mechanism - intelligence amplification (IA). The management of complexity requires the optimal orchestration of natural intelligence and artificial intelligence, the partnership of the organism and the mechanism.