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Abstract: The rise of “Big Data” analytics in the private sector poses new challenges for privacy advocates. Through its reliance on existing data and predictive analysis to create detailed individual profiles, Big Data has exploded the scope of personally identifiable information (“PII”). It has also effectively marginalized regulatory schema by evading current privacy protections with its novel methodology. Furthermore, poor execution of Big Data methodology may create additional harms by rendering inaccurate profiles that nonetheless impact an individual’s life and livelihood. To respond to Big Data’s evolving practices, this Article examines several existing privacy regimes and explains why these approaches inadequately address current Big Data challenges. This Article then proposes a new approach to mitigating predictive privacy harms—that of a right to procedural data due process. Although current privacy regimes offer limited nominal due process-like mechanisms, a more rigorous framework is needed to address their shortcomings. By examining due process’s role in the Anglo-American legal system and building on previous scholarship about due process for public administrative computer systems, this Article argues that individuals affected by Big Data should have similar rights to those in the legal system with respect to how their personal data is used in such adjudications. Using these principles, this Article analogizes a system of regulation that would provide such rights against private Big Data actors.


Stanford Law Review | 09.03.13

It’s Not Privacy, and It’s Not Fair

Cynthia Dwork, Deirdre K. Mulligan

In the Stanford Law Review symposium issue on privacy and big data (September 2013), Cynthia Dwork and Data & Society advisor Deirdre Mulligan argue that “privacy controls and increased transparency fail to address concerns with the classifications and segmentation produced by big data analysis.” “If privacy and transparency are not the panacea to the risks posed by big data,” they ask, “what is?” They offer a quartet of approaches/areas of focus.


paper | 09.21.11

Six Provocations for Big Data

danah boyd, Kate Crawford

This essay offers a multi-discplinary social analysis of the “Big Data” phenomenon with the goal of sparking a conversation, and it continues to provide a point of reference for the launch and development of Data & Society.

Abstract: The era of “Big Data” has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and many others 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 information from Twitter, Google, Verizon, 23andMe, Facebook, Wikipedia, and every space where large groups of people leave digital traces and deposit data. Significant questions emerge. Will large-scale analysis of DNA help cure diseases? Or will it usher in a new wave of medical inequality? Will data analytics help make people’s access to information more efficient and effective? Or will it be used to track protesters in the streets of major cities? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means? Some or all of the above?


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