Big data privacy: The datafication of personal information

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Big data privacy: The datafication of personal information. / Mai, Jens-Erik.

In: The Information Society, Vol. 32, No. 3, 13.04.2016, p. 192-199.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Mai, J-E 2016, 'Big data privacy: The datafication of personal information', The Information Society, vol. 32, no. 3, pp. 192-199. https://doi.org/10.1080/01972243.2016.1153010

APA

Mai, J-E. (2016). Big data privacy: The datafication of personal information. The Information Society, 32(3), 192-199. https://doi.org/10.1080/01972243.2016.1153010

Vancouver

Mai J-E. Big data privacy: The datafication of personal information. The Information Society. 2016 Apr 13;32(3):192-199. https://doi.org/10.1080/01972243.2016.1153010

Author

Mai, Jens-Erik. / Big data privacy: The datafication of personal information. In: The Information Society. 2016 ; Vol. 32, No. 3. pp. 192-199.

Bibtex

@article{7fcee79e71df453cbe481ca5cbfa60d6,
title = "Big data privacy: The datafication of personal information",
abstract = "In the age of big data we need to think differently about privacy. We need to shift our thinking from definitions of privacy (characteristics of privacy) to models of privacy (how privacy works). Moreover, in addition to the existing models of privacy—the surveillance model and capture model—we need to also consider a new model: the datafication model presented in this article, wherein new personal information is deduced by employing predictive analytics on already-gathered data. These three models of privacy supplement each other; they are not competing understandings of privacy. This broadened approach will take our thinking beyond current preoccupation with whether or not individuals{\textquoteright} consent was secured for data collection to privacy issues arising from the development of new information on individuals' likely behavior through analysis of already collected data—this new information can violate privacy but does not call for consent.",
keywords = "Faculty of Humanities, Big data, Datafication, Personal information, Privacy",
author = "Jens-Erik Mai",
year = "2016",
month = apr,
day = "13",
doi = "10.1080/01972243.2016.1153010",
language = "English",
volume = "32",
pages = "192--199",
journal = "Information Society",
issn = "0197-2243",
publisher = "Taylor & Francis",
number = "3",

}

RIS

TY - JOUR

T1 - Big data privacy: The datafication of personal information

AU - Mai, Jens-Erik

PY - 2016/4/13

Y1 - 2016/4/13

N2 - In the age of big data we need to think differently about privacy. We need to shift our thinking from definitions of privacy (characteristics of privacy) to models of privacy (how privacy works). Moreover, in addition to the existing models of privacy—the surveillance model and capture model—we need to also consider a new model: the datafication model presented in this article, wherein new personal information is deduced by employing predictive analytics on already-gathered data. These three models of privacy supplement each other; they are not competing understandings of privacy. This broadened approach will take our thinking beyond current preoccupation with whether or not individuals’ consent was secured for data collection to privacy issues arising from the development of new information on individuals' likely behavior through analysis of already collected data—this new information can violate privacy but does not call for consent.

AB - In the age of big data we need to think differently about privacy. We need to shift our thinking from definitions of privacy (characteristics of privacy) to models of privacy (how privacy works). Moreover, in addition to the existing models of privacy—the surveillance model and capture model—we need to also consider a new model: the datafication model presented in this article, wherein new personal information is deduced by employing predictive analytics on already-gathered data. These three models of privacy supplement each other; they are not competing understandings of privacy. This broadened approach will take our thinking beyond current preoccupation with whether or not individuals’ consent was secured for data collection to privacy issues arising from the development of new information on individuals' likely behavior through analysis of already collected data—this new information can violate privacy but does not call for consent.

KW - Faculty of Humanities

KW - Big data

KW - Datafication

KW - Personal information

KW - Privacy

UR - http://jenserikmai.info/Papers/2016_BigDataPrivacy.pdf

U2 - 10.1080/01972243.2016.1153010

DO - 10.1080/01972243.2016.1153010

M3 - Journal article

VL - 32

SP - 192

EP - 199

JO - Information Society

JF - Information Society

SN - 0197-2243

IS - 3

ER -

ID: 160530286