While this week’s reading demonstrated that “information overload” is hardly a new phenomena, attempts to address this predicament through sophisticated databases and interlinked associations are relatively more modern. From Otlet to Ranganathan, attempts to classify and control knowledge appear to pick up steam in the late nineteenth to the early twentieth century. Looking back on their efforts there is almost a nostalgia for the past and this belief that we could eventually contain and command access to all knowledge in the world. Easy, right?
And yet today Google’s algorithms push us closer to this notion of a “utopia,” where all knowledge is easily retrievable. With the emergence of concepts like the semantic web we can theoretically create machines that learn to think, “as we may think.” For anyone who has ever googled something extraordinarily ridiculous or extremely specific (e.g. “adverbs that begin with the letter de,” “birthday presents for a thirty-year-old food snob” or “how do I figure out my life’s purpose?”), it’s clear that Google has become highly sophisticated in the ways it interprets search queries and suggests information.
And yet, the underpinnings of their algorithms and search structures are somewhat of a “black box” for most individuals. It seems that in many ways, we are becoming less cognizant of the underlying epistemological infrastructures. As Michel Foucault notes, when we consider classification systems we must ask, “What is the ground on which we are able to establish the validity of this classification with complete certainty? On what ‘table,’ according to what grid of identities, similitudes, analogies, have we become accustomed to sort out so many different and similar things?”
Even as the web creates “useful trails” in the vast array of information, I wonder how we can all become more active agents in seeing the artificiality, permeability, and even missed potentialities of our new “search-based” culture. Rather than delegating intellectual authority to “smart machines,” is there a future scenario in which we can develop technology that doesn’t simply simulate but can also stimulate new thought.