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    Algorithmic surveillance: the collection conundrum

    Murphy, Maria Helen (2017) Algorithmic surveillance: the collection conundrum. International Review of Law, Computers & Technology, 31 (2). pp. 225-242. ISSN 1360-0869

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    Supporters of increased surveillance see tremendous potential in the ever increasing creation, collection, and retention of personal data. Most acknowledge that the massive collection of information also creates challenges where the collection outpaces the ability to meaningfully process the data. Increased processing power and more finely tuned algorithms are often portrayed as the solution to this haystack conundrum. While a human may struggle to find the needle in an overflowing haystack of disordered information, powerful computers can take a logical and structured approach that will make the haystack eminently more searchable. This article evaluates this premise from a human rights perspective and considers whether algorithmic surveillance systems can be designed to be compatible with the right to privacy. In addition to assessing the incongruity between traditional safeguards (such as foreseeability and accountability) with algorithmic surveillance, this article also confronts the problem of initial collection and addresses the contention that well-defined algorithmic search can effectively limit the intrusiveness of surveillance. Evolution in the case law of the European Court of Human Rights and the Court of Justice of the European Union will be factored into this analysis.

    Item Type: Article
    Keywords: Algorithms; surveillance; privacy;
    Academic Unit: Faculty of Social Sciences > Law
    Faculty of Social Sciences > Research Institutes > Maynooth University Social Sciences Institute, MUSSI
    Item ID: 11681
    Identification Number:
    Depositing User: Maria Murphy
    Date Deposited: 12 Nov 2019 14:23
    Journal or Publication Title: International Review of Law, Computers & Technology
    Publisher: Taylor & Francis
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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