Uncertain Archives: Approaching the Unknowns, Errors and Vulnerabilities of Big Data through Cultural Theories of the Archive

Research output: Contribution to journalJournal articleResearchpeer-review

Daniela Agostinho, Catherine D'Ignazio, Annie Ring, Nanna Thylstrup, Kristin Veel

We are surrounded by digital apparatuses that continuously capture, process, and archive social and material information: from global search engines to local smart cities, from public health monitoring to personal self-tracking technologies. Although the use of big data emerged from the human desire to acquire more knowledge and master more information, and to eliminate human error in large-scale information management, it has become clear in recent years that big data technologies, and the archives of data they accrue, bring with them new and important uncertainties in the form of new biases, systemic errors, and, as a result, new ethical challenges that require urgent attention and analysis. This collaboratively-written article outlines the conceptual framework of the research collective Uncertain Archives to show how cultural theories of the archive can be meaningfully applied to the empirical field of big data. More specifically, the article argues that this cultural-theoretical approach can help research going forward to attune to and address the uncertainties present in the storage and analysis of large amounts of information. By focusing on the notions of the unknown, error, and vulnerability, we reveal a set of different, albeit entwined, configurations of archival uncertainty that emerge along with the phenomenon of big data use, which we regard as central to understanding the conditions of the digitally networked data archives that have become a crucial component of today’s cultures of surveillance and governmentality.
Original languageEnglish
JournalSurveillance & Society
Publication statusAccepted/In press - 2019

ID: 210363746