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But there is a tension between what we understand these algorithms to be, what we need them to be, and what they in fact are. We do not have a sufficient vocabulary for assessing the intervention of these algorithms. We’re not adept at appreciating what it takes to design a tool like Trends – one that appears to effortlessly identify what’s going on, yet also makes distinct and motivated choices. We don’t have a language for the unexpected associations algorithms make, beyond the intention (or even comprehension) of their designers (Ananny 2011). Most importantly, we have not fully recognized how these algorithms attempt to produce representations of the wants or concerns of the public, and as such, run into the classic problem of political representation: who claims to know the mind of the public, and how do they claim to know it?
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Beyond search, we are surrounded by algorithmic tools that offer to help us navigate online platforms and social networks, based not on what we want, but on what all of their users do. When Facebook, YouTube, or Digg offer to mathematically and in real time report what is “most popular” or “liked” or “most viewed” or “best selling” or “most commented” or “highest rated,” they are curating a list whose legitimacy is built on the promise that it has not been curated, that it is the product of aggregate user activity itself. When Amazon recommends a book based on matching your purchases to those of its other customers, or Demand Media commissions news based on aggregate search queries (Anderson 2011), their accuracy and relevance depend on the promise of an algorithmic calculation paired with the massive, even exhaustive, corpus of the traces we all leave.
We might, then, pursue the question of the algorithm’s politics further. The Trends algorithm does have criteria built in: criteria that help produce the particular Trends results we see, criteria that are more complex and opaque than some users take them to be, criteria that could have produced the absence of the term #occupywallstreet that critics noted. But further, the criteria that animate the Trends algorithm also presume a shape and character to the public they intend to measure, and in doing so, help to construct publics in that image.