In critiquing evolutionary theory, Collins (1988) rightly noted that most evolutionary theorists did not perceive any stage except the present one with the obvious exception of Marx and Engels (Feuer 1959). In some respects, this is a mischaracterization of Marx and Engels because the stage they predict after capitalism is a socialist paradise or utopia. I can assure the reader that I am not promising any rose garden at the end of the third stage of knowledge creation. Instead, I predict that there will be a fourth stage of knowledge creation, which punctuates the preceding equilibria, presenting new adaptive problems requiring further innovative institutional transformations. This kind of prediction is quite different from the technological forecasting that became quite popular in the 1970s and 1980s. In this forecasting, the attempt was made to anticipate specific new technologies, most of them beneficial. A typical example was the idea of cheap hydrogen fusion energy. After 40 years of research, the estimate of the experts is that it will always be too expensive to produce; thus, alas, another rose that will probably never bloom. I want to avoid any kind of specific technological forecasting and, rather, suggest some broad contours of what might be characteristic of the next stage of knowledge creation. In the process, I review the main underlying argument about the causes of each stage of knowledge creation and project it into the future. My sense of this future voyage contains enormous theoretical risks, remains quite speculative, and should be treated with considerable skepticism, which (again) remains a necessary postmodern attitude. However, I embark on what might seem like a senseless voyage for the benefit of my grandchildren and great- grandchildren so that they might try and prepare themselves for life in the middle of this century.

The overarching logic of the argument presented in Chapter One is that it becomes increasingly difficult to create new knowledge in each of its four components: machines, including tools and techniques; software and operating instructions; skills and expertise; and models and theories. To produce this new knowledge in the form of solutions also requires much more complex knowledge- production systems.