CRITICAL QUESTIONS FOR BIG DATA (boyd & crawford, 2012)

“The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians political scientists, bio-informaticists, sociologists, and other scholars are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions. Diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people. Significant questions emerge. Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements? Or will it be used to track protesters and suppress speech?”

Critical questions for big data




“This article investigates how the new spirit of capitalism gets inscribed in the fabric of search algorithms by way of social practices. Drawing on the tradition of the social construction of technology (SCOT) and 17 qualitative expert interviews it discusses how search engines and their revenue models are negotiated and stabilized in a network of actors and interests, website providers and users first and foremost. It further shows how corporate search engines and their capitalist ideology are solidified in a socio-political context characterized by a techno-euphoric climate of innovation and a politics of privatization. This analysis provides a valuable contribution to contemporary search engine critique mainly focusing on search engines’ business models and societal implications. It shows that a shift of perspective is needed from impacts search engines have on society towards social practices and power relations involved in the construction of search engines to renegotiate search engines and their algorithmic ideology in the future”.

Algorithmic Ideology



“Algorithms play an increasingly important role in selecting what information is considered most relevant to us, a crucial feature of our participation in public life. Search engines help us navigate massive databases of information, or the entire web. Recommendation algorithms map our preferences against others, suggesting new or forgotten bits of culture for us to encounter. Algorithms manage our interactions on social networking sites, highlighting the news of one friend while excluding another’s. Algorithms designed to calculate what is “hot” or “trending” or “most discussed” skim the cream from the seemingly boundless chatter that’s on offer. Together, these algorithms not only help us find information, they provide a means to know what there is to know and how to know it, to participate in social and political discourse, and to familiarize ourselves with the publics in which we participate. They are now a key logic governing the flows of information on which we depend, with the “power to enable and assign meaningfulness, managing how information is perceived by users, the ‘distribution of the sensible.'” (Langlois 2012)

The relevance of algorithms


RAW DATA IS AN OXYMORON (edited by Gitelman, 2013)

“We live in the era of Big Data, with storage and transmission capacity measured not just in terabytes but in petabytes (where peta denotes a quadrillion, or a thousand trillion). Data collection is constant and even insidious, with every click and every “like” stored somewhere for something. This book reminds us that data is anything but “raw,” that we shouldn’t think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted”


LUCIANO FLORIDI (Big Data and Their Epistemological Challenge, Philosophy & Technology, 2012)

“Despite the importance of the phenomenon, it is unclear what exactly the term “big data” means and hence refers to. The aforementioned document specifies that: “The phrase ‘big data’ in this solicitation refers to large, diverse, complex, longitudinal, and/or distributed data sets generated from instruments, sensors, Internet transactions, email, video, click streams, and/or all other digital sources available today and in the future.” You do not need to be an analytic philosopher to find this both obscure and vague” (Floridi, 2012).


BRUNO LATOUR (“The Whole is Always Smaller Than Its Parts”, 2012)

Abstract: In this paper we argue that the new availability of digital data sets allows one to revisit Gabriel Tarde’s (1843-1904) social theory that entirely dispensed with using notions such as individual or society. Our argument is that when it was impossible, cumbersome or simply slow to assemble and to navigate through the masses of information on particular items, it made sense to treat data about social connections by defining two levels: one for the element, the other for the aggregates. But once we have the experience of following individuals through their connections (which is often the case with profiles) it might be more rewarding to begin navigating datasets without making the distinction between the level of individual component and that of aggregated structure. It becomes possible to give some credibility to Tarde’s strange notion of ‘monads’. We claim that it is just this sort of navigational practice that is now made possible by digitally available databases and that such a practice could modify social theory if we could visualize this new type of exploration in a coherent way.