Abstract
Who are we online? This is the main question Cheney-Lippold’s book investigates and the concise answer is: we are not who we think we are. While many of us might have the idea that our digital identities are accurate representations of ourselves, the author makes a convincing argument that this is not the case. On the contrary, he writes that our digital identity is deeply rooted in functionalistic models where “our data is spoken for with a language fashioned from these models” (p. 48). Drawing on a number of valuable examples, the book points towards the existing (and partly frightening) gap between the ambiguity of everyday life experiences and the simplicity of computational models in an effort to capture and make sense of these.
The book is structured around four main themes. The first theme, categorization, engages with the idea of metadata and illustrates how conclusions are drawn from such classification systems. The second theme, control, explores how authoritative relationships are established and how decisions made from big data analyses are surrounded by a certain aura of truth. The third theme, subjectivity, examines the concept of algorithmic citizenship and the assumptions that citizens have to reckon with when going online. The fourth theme, privacy, engages with the historical roots of privacy and makes a call for “a privacy that extends beyond our individual bodies, that accepts the realities of ubiquitous surveillance, and that defends the ‘right to be alone’ even, and especially, when we are made of data” (p. 236).
Overall We Are Data is an inspiring and thought-provoking book to read, especially for those interested in the social, political, and cultural aspects of data. It draws on a wide range of well-known literature in the field of Internet and algorithm studies and further engages deeply with the philosophical aspects of the presented themes. It is, hence, not an easy book to read but for those taking the time to immerse themselves in the author’s line of argumentation, it is certainly very rewarding. As such, while not directly related to mobile media, all the examples given can easily be understood from a more general communication perspective, and no prior knowledge about data and algorithms is required.
The examples presented in the book are persuasive. However, due to the long process of writing such a book, they may seem a little outdated. The critical reader might ask if the computational models presented are still representative given the fast pace of technological development; and this is exactly the point: It is not about the models themselves as they are merely examples. It is about the layers of data these models produce and provide for our world. To explore, describe, and examine these layers of datafied knowledge is the core contribution of the Cheney-Lippold’s book to the field of media and communication.