Society and Technological Control: A Critical Review of Models of Technological Change in Ceramic Studies

Abstract

The use of evolution as either analogy or theory in ceramic change artificially imposes a view of technology that is directed. The use of progress has led to a tendency to equate technological change with technological improvement, as if change were unidirectional. This improvement is usually measured by modern standards of industrialization, such as increasing standardization, increasing speed of production, increasing quantity of production, and the overall increasing formality of the workshop. Within models that employ an evolutionary paradigm there is the implicit notion that: a) technology change, when it occurs, only occurs towards improvement; b) improvement occurs toward the most logical, efficient solution to a technological problem; and c) such a solution is rooted in fundamental scientific "truths" or "facts," which scientists or technicians "discover." Over the past twenty years, social scientists studying the development of modern technology and society have questioned the usefulness of evolution as a model for change. A critical appraisal of technologically determinist history of scientific discovery has found that important discoveries are frequently credited with fundamentally changing the course of history. The evidence of modern history and ethnography, however, shows that cultural values and embedded beliefs may be more powerful in selecting and directing developing technologies than any external factors. European archaeologists van der Leeuw, Petréquin, and Loney, among others, are now applying the findings of the techno-sociologists to the development of ancient pottery production. Their perspective on ancient technology takes into account personal choice as well as ecological resources and economic organization. The approach of European archaeologists permits the investigation of the varied trajectories of ancient ceramic technology without resorting to self-perpetuating, internally self-generating models of biological evolution.