Datafiction, dataism, and dataveillance: Big Data between scientific paradigm and ideaology

Text Exploration

In this article, the author describes how people have gotten used to providing metadata to the state and to large corporations without questioning what they are providing and how it will be used. The data, then, is presented as objective, and used for various purposes that may not be expected or desired.

The author references Edward Snowden’s whistle-blowing, arguing that it served as a “wakeup call” for citizens who weren’t aware of the data that the government had gathered about them (or what it was used for.) Citizens had grown accustomed to data as currency—trading data for various products and services—and this is a normalization of what can be thought of as datafication: accessing, understanding and monitoring people’s behavior. Dataism is a similar phenomenon by which large entities come to believe in the power of that data, and in order to gain access to it, they use methods of dataveillance.

Facebook, Google, and other social media companies argue that they leverage collected data as a way of showing popular sentiment, and that their collection and use of data is neutral. However, the data itself has been gathered, organized, and interpreted in support of a motive (typically to measure, manipulate, and monetize online behavior), and to call the organization’s activities objective is an unfair representation of their intrusion into usage behavior. Data is always considered through an interpretative frame, and “making sense of patterns thus requires critical interrogation.” Someone is doing the interrogating, with a goal, and from a perspective, and this then makes the data biased and potentially weaponized.

These corporations have become intertwined with government, as they claim that they are bound to rules outside of their control and simultaneously lobby for legal change to support their strategic objectives. Academia, too, can be considered a part of a “tripartite alignment of forces,” as researchers leverage the same form of data in an effort to make seemingly unbiased data-driven claims about behavior.

The author concludes that, because of this conglomerate mutual dependency and a widespread view of data as a neutral currency, the “credibility of the entire ecosystem” is at stake.