Attempting to generally define the influence of culture on rates of innovation poses an extremely difficult proposition. The sheer scope of the issue, spanning centuries of innovation and human culture, proves to be quite daunting. The traditional approach to such broadly defined questions involves focusing on either a particular aspect of culture or specific period of time, oftentimes both. Although the conclusions drawn from these simplifications may hold some explanatory power, they fail to adequately address the initial issue.
The standard approach to broad topics of inquiry involves narrowly redefining the complex concept of culture into one of its constituent parts, such as religion. Even with this approach, it is difficult to draw conclusions that are consistent throughout history. History seems to offer a piece of counter-evidence for each historical fact in support of a particular theory. Again, the tendency at this point is to further reduce the scope of the initial question to not only a single facet of culture, but also a limited period of time. This approach to broad questions, such as the effect of culture on technology, tends to overemphasize the causal role of cultural factors. Reductionistic theories can be fitted around a constrained set of historical data. This historic fitting imparts a high degree of explanatory power to such theories. However, questions such as the influence of culture on technology are interesting because of their broad nature and defy the neat explanations offered by reductionistic models.
Rather than targeting a specific aspect of culture or time period for analysis, this essay utilizes a more general approach. Under this framework, the concept of culture is treated as an amorphous, single entity rather than being divided into more specific categories. The term culture possesses a remarkable ability to defy clear definition owing to its numerous constituents. Subsequently, this general analysis focuses primarily on the rate of innovation. Instead of attempting to extrapolate shifts in the rate of technological progress due to culture, this model attempts to calculate the extent to which innovation rates can be attributed to cultural influences. The difference is subtle. Typically a reductionistic analysis begins with cultural factors as a given and attempts to explain technological change in terms of these cultural factors. The viewpoint advocated here, begins with the rate of innovation and attempts to deduce how much of the rate can be explained by cultural factors.
The benefits of this type of general analysis become most apparent when exploring the mechanisms behind the rate of innovation. Innovation is a complex phenomenon involving countless economic, social, political, and cultural variables. On an individual level, the process of invention requires large expenditures of physical and human capital for an uncertain payoff. The incentives for an individual to innovate are determined by the magnitude and possibility of their gains. Not surprisingly, the inventor cannot accurately predict the expected value of his invention nor subsequently allocate his resources effectively. Without the ability to predict the expected value of an invention, it is not far-fetched to assume that inventors rely upon the past success of other inventors as a rough predictor of an invention's expected value. Thus historic innovation fosters future innovation. Joel Mokyr dubbed this positive feedback loop the imitation effect (Mokyr, 255). Mokyr goes on to describe several other types of positive feedback loops inherent in technological progress including chains of inspiration and clustering. These positive feedback loops imply that technologically successful cultures generate high rates of future technological innovation. At this point, the circular logic prevents differentiating between the causal effects of cultural variables on innovation rates with positive feedback generated by mechanisms such as the imitation effect.
The primary conclusion stemming from this general analysis framework states that the rate of innovation is determined by countless factors including past technological performance. The unknown interaction between the variables and the existence of feedback loops effectively mask the influence of culture on technology. Redefining culture more narrowly or limiting the analyzed time period merely provides the impression of historical accuracy. Effectively isolating the effects of an independent variable, in this case culture or a narrow aspect of culture, proves to be impossible as long as the dependent variable, rates of technological progress, contains complex elements of uncertain magnitude. Accordingly, an attempt to define the influence of culture on technology, through a reductionistic framework, risks misattributing changes in innovation to cultural factors.