Cukier and Schoenberger’s central claim is to analyze, through a consideration of the analog and digital eras, society’s place within the big data phenomenon and what principles society ought to establish to welcome a future where big data does not render harm. The book is comprised of ten chapters, five of which contend the positive impacts of big data on an array of business sectors, and four which highlight some of the measures society ought to take for the future to come of big data. Chapters two to four outline three mutually intertwined shifts caused as a result of the big data phenomenon. The first of these shifts suggest how cheaper storage power and new technologies have made feasible and eased the data-gathering process, enabling one to harness larger volumes of data in order to delve deeper into the granularities of one’s hypotheses. Furthermore, the second shift considers the move away from the analog era’s need for exactitude, and high quality of smaller sets of data to the digital era’s hailing of messier, more inaccurate, and greater sets of data to enable one to divine the general trend of the data. The third shift moves away from the analog era’s quest for causality, towards the embrace of correlations as the authors believe that data can speak for itself, thus contending that a focus on the “what” rather than the “why” of a correlation will render better and less biased results. These three shifts lead Cukier and Schoenberger to discuss, in chapter five, the concept of datafication, suggesting how it has become a powerful practice for enriching researchers and large corporations’ understanding of society’s social behaviors. Chapter six considers how data has increasingly become a valuable and essential intangible asset needed to efficiently run a business, suggesting how many businesses are reusing, and finding twofers to make greater use of the data. Chapters seven to nine consider some of the risks resulting from an overreliance on big data and the guidelines that ought to be taken in order to mitigate injustice. The first of these is the risk of an individual being punished on the basis of what their data shows. The second risk fears a dictatorship of data, where too much power is given to predictive algorithms and big data. The third risk suggests how surveillance is inevitable as choosing to preserve one’s privacy might raise a government’s suspicion. The fourth risk, suggests that an overreliance on prediction will shape a future devoid of creativity and originality where decisions are all made on the basis of patterns and correlations. As a result of these risks, the authors have outlined some of the measures of control that ought to be taken. Firstly, there is a need to redefine the logic of justice in order to maintain freedom and protect human agency. Secondly, the authors believe there is a need for impartial professionals who can interpret the validity of predictive algorithms in order to mitigate injustice, and prevent large corporations from making unfounded judgments on the basis of big data patterns.
Chapter 10, concludes by suggesting how society, business, governments, and academia have all undergone a transformation as a result of the big data phenomenon. There has been a notable shift in the understanding of knowledge, in the accuracy of the data, and in the ease of gathering large sets of data to explore societal, economic and behavioral matters more effectively. However, this book brings forth a limitation in trying to avoid a stance of technological solutionism. Although Cukier and Schoenberger present some of the risks and possible guidelines to be established, they fail to provide a more profound, resound and substantial discussion of the threats posed by big data. Although it is important to celebrate the advancements in technology, it is just as important to bring forth a discussion over the consequences of big data upon society. In spite of this limitation, the book’s overarching discussion and comparison of the analog and digital eras has been useful for understanding the transformation that big data has undergone. Further, Cukier and Schoenberger’s book will serve useful in setting the grounds for the origins of big data discourse. Cukier and Schoenberger’s stance significantly counters the views proposed by boyd and Crawford. For instance, whereas Cukier and Schoenberger believe that large amounts of data rather than small portions of them render better results, boyd and Crawford, in their third provocation suggest how value lies in the quality of the data and not in the quantity.