Information Spreads. So what?
In my last post I made the argument that the Humanities needs to develop a rigorous and precise language to discuss culture, a model straight out of Mathematics. What I didn’t include in my last post, though, was any specific positive outcome for the Humanities in adopting this course. I suggested that it would open a bridge between the Humanities and the STEM disciplines, but that does not seem like it will be the cherry on top that gets scholars and professors deeply ingrained in the traditional system to change their ways.
This lack of a metaphorical cherry on top is the largest problem facing the networked view of culture that I would like to promote; the spread of information is simply not sexy. But, even if its not initially appealing, the payoff from viewing culture as a network is impressive.
First, considering culture as a network gives us a basis for a more accurate and consistent version of the concept of influence. Influence no longer has to be a primarily interpretative feature in art. Instead, by looking for the networked relationships in culture, we can speak about art in regards to offspring and precise lineages. We can examine, much more accurately, how an idea or technique moves through culture and changes over time. As critics, we would gain the power to fully study whole pieces (themes, techniques, etc.). The problem of scaling up our research could be eliminated.
Second, in establishing a model for how culture operates like a network, we would gain the ability to identify relationships that we may not otherwise notice. If we can establish the model and visualize it effectively, we will see connections that will not make any sense to us. These connections, and their offshoots, will be the fascinating problems that Humanities scholars should be exploring and trying to solve. If our study of culture up to this point has concluded anything, it is that the ways we express ourselves in art are important representations of a variety of experiences. Therefore, if we find works that are unexpectedly technically similar, we need to study the relationships to learn more about the expression of experience, the material recording of culture.
Finally, just as the network model of culture will lead us to more interesting problems, it will also trivialize much of the difficulties the Humanities currently face. It can relate history to literature and art. It can, when used as the basis for developing digital tools, lead to the avoidance of having to carry out the actual search for the formal techniques. Right now, the Humanities are limited by the human limitations on identifying patterns at scale. We simply cannot process the information necessary to identify the technical similarities in art if we are dealing with more than a small handful of works. Computers, alternatively, can be programmed to find these patterns in an efficient manner and to store the results in such a way that they can be queried and searched by scholars. When we arrive at this reality, scholars will no longer have to spend their time trying to find similarities, and instead will be free to devote all of their time to analyzing and explaining the patterns.
Effectively, then, a networked model of culture frees the scholars, critics, and teachers to focus on the more important aspects of their work. It allows them to do everything that they already do, but better. Of course, we have so much work to do to popularize this model and develop the tools to take advantage of looking at culture in this way. But, if we recognize the possibilities that this model of culture and art affords us, it will be easier to develop support and generate funding and opportunities for this model to grow and have a chance.