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Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Stanford, CA: Stanford University.
https://web.stanford.edu/~hastie/Papers/ESLII.pdf
https://doi.org/10.1007/978-0-387-84858-7

has been cited by the following article:

• TITLE: Personal Data v. Big Data in the EU: Control Lost, Discrimination Found

  AUTHORS: Maria Bottis, George Bouchagiar

  KEYWORDS: Personal Data, Consent, Control, Discrimination

  JOURNAL NAME: Open Journal of Philosophy, Vol.8 No.3, May 11, 2018

  ABSTRACT: We live in the Big Data age. Firms process an enormous amount of raw, unstructured and personal data derived from innumerous sources. Users consent to this processing by ticking boxes when using movable or immovable devices and things. The users’ control over the processing of their data appears today mostly lost. As algorithms sort people into groups for various causes, both legitimate and illegitimate, fundamental rights are endangered. This article examines the lawfulness of the data subject’s consent to the processing of their data under the new EU General Data Protection Regulation. It also explores the possible inability to fully anonymize personal data and provides an overview of specific “private networks of knowledge”, which firms may construct, in violation of people’s fundamental rights to data protection and to non-discrimination. As the Big Data age is here to stay, both law and technology must together reinforce, in the future, the beneficent use of Big Data, to promote the public good, but also, people’s control on their personal data, the foundation of their individual right to privacy.