In recent years, technology and business writers have stumbled over each other to show how new technologies in data collection and management are revolutionizing our lives. The claim in Viktor Mayer-Schönberger's and Kenneth Cukier's bestselling book, Big Data: A Revolution That Will Transform How We Work, Think, and Live (2013)—that "the world of big data is poised to shake up everything from businesses and the sciences to healthcare, government, education, economics, the humanities, and every other aspect of society" (11)—is but one example of the great expectations resting on recent developments in computation and informatics. But if the technology behind the big data revolution is new, the idea behind it is not. There is an uncanny resemblance between claims made on behalf of big data and those made by naturalist fiction more than a century ago. What the influential MIT computer scientist Alex Pentland in Social Physics (2014) calls "living laboratories"—i.e., the use of social data obtained through mobile devices and sensors to "watch human organizations evolve on a microsecond-by-microsecond basis" (121)—echoes the Sekundenstil (second-by-second style) of German naturalists like Arno Holz seeking to describe every detail of reality as it unfolds, but also Émile Zola's view of the naturalist novel as modeled on the laboratory experiment for mapping our desires and habits. Pentland's use of big data to "observe humans in just the same way we observe apes or bees and derive rules of behavior, reaction, and learning" (190) has an unmistakable naturalist ring to it. His observation that "we are now coming to realize that human behavior is determined as much by social context as by rational thinking or individual desires" (59) is hardly news to anyone who has ever read a naturalist novel. There are also striking similarities between the organizing natural [End Page 1] metaphors of big data discourse, the "oceans," "mountains," "floods," and "avalanches" of data in Mayer-Schönberger's and Cukier's book, and Frank Norris's representations of wheat as a natural force in The Octopus (1901) and The Pit (1903). Even the moral thrust behind collecting all of this data—to "predict and mitigate financial crashes, detect and prevent infectious disease, use our natural resources more wisely, and encourage creativity to flourish and ghettos to diminish" (Pentland 216)—recalls the reform agendas of the Progressive Era that American literary naturalism had been associated with.
What are we to do with these parallels? First, the commonalities between the discourse of big data today and naturalist literature deflate some of the claims about the revolutionary newness of the era of big data. To be sure, historians of science and statistics have long traced the triumphal march of quantitative methods through the natural and social sciences to society at large. Far from being new, the recent hype surrounding the power of data takes us back to the beginnings of modern science. Data-driven research emerged in the seventeenth and eighteenth centuries with an increasing desire for predictability as society grew more complex and the power of providential explanations waned. It was not until the late nineteenth century, however, that quantification became an epistemological paradigm reaching from the natural to the social sciences—with profound implications for culture and literature. In using a term coined by Auguste Comte for the title of his book, Pentland implicitly acknowledges the historical debt of big data to the probabilistic revolution in the sciences. Big data's dictum to let data speak for itself evokes nineteenth-century desires for objectivity, the "blind sight" that "bears no trace of the knower—knowledge unmarked by prejudice or skill, fantasy or judgment, wishing or striving" (Daston and Galison 17). The scientific neutrality that data promises has long served political and institutional interests by offering a way to mediate social tensions and facilitate communication. A historical perspective on recent debates on the role of data thus places them in the context of a larger discursive continuum, and it sheds light on the political and institutional conditions underlying the desire for ever more and better data.
Insightful as the history of...