Slaves to Big Data. Or Are We?

被引:6
|
作者
Hildebrandt, Mireille [1 ]
机构
[1] Radboud Univ Nijmegen, Inst Comp & Informat Sci, Smart Environm Data Protect & Rule Law, Nijmegen, Netherlands
来源
关键词
Big Data; artificial intelligence; monetisation of personal data; user-centric personal data management; double contingency;
D O I
10.7238/idp.v0i17.1977
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
In this contribution, the notion of Big Data is discussed in relation to the monetisation of personal data. The claim of some proponents, as well as adversaries, that Big Data implies that 'n = all', meaning that we no longer need to rely on samples because we have all the data, is scrutinised and found to be both overly optimistic and unnecessarily pessimistic. A set of epistemological and ethical issues is presented, focusing on the implications of Big Data for our perception, cognition, fairness, privacy and due process. The article then looks into the idea of user-centric personal data management to investigate to what extent it provides solutions for some of the problems triggered by the Big Data conundrum. Special attention is paid to the core principle of data protection legislation, namely purpose binding. Finally, this contribution seeks to inquire into the influence of Big Data politics on self, mind and society, and asks how we can prevent ourselves from becoming slaves to Big Data.
引用
收藏
页码:27 / 44
页数:18
相关论文
共 50 条
  • [1] BIG DATA. BIG DATA WITH NETEZZA
    Velicanu, Manole
    Titirisca, Aurelian
    [J]. INTERNATIONAL CONFERENCE ON INFORMATICS IN ECONOMY, 2013, : 377 - 380
  • [2] Big Data. Big Problem?
    Harrop, Clare
    Dallman, Aaron R.
    Boyd, Brian A.
    [J]. AUTISM RESEARCH, 2021, 14 (02) : 238 - 239
  • [3] The politics of big data. Big data, big brother?
    Mager, Astrid
    [J]. INFORMATION COMMUNICATION & SOCIETY, 2019, 22 (10) : 1523 - 1525
  • [4] Big Data. A briefing
    Todde, Virginia
    Giuliani, Alessandro
    [J]. ANNALI DELL ISTITUTO SUPERIORE DI SANITA, 2018, 54 (03): : 174 - 175
  • [5] Big data. Big potential. Big problems?
    West, Stephen W.
    Clubb, Jo
    Blake, Tracy A.
    Fern, James
    Bowles, Harry
    Dalen-Lorentsen, Torstein
    [J]. BMJ OPEN SPORT & EXERCISE MEDICINE, 2024, 10 (02):
  • [6] Big data. A very short introduction
    Wilson, T. D.
    [J]. INFORMATION RESEARCH-AN INTERNATIONAL ELECTRONIC JOURNAL, 2017, 22 (04):
  • [7] Collection and utilization of oncology big data.
    Pant, Shubham
    Owonikoko, Taofeek Kunle
    Diefenbach, Catherine S. Magid
    Kim, Sungjin
    Chen, Zhengjia
    Towle, Elaine L.
    Pierce, Lori J.
    Mileham, Kathryn Finch
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2017, 35
  • [8] Algorithms and Big Data. The Rules and Principles of Robotics
    Mangiameli, Agata C. Amato
    [J]. RIVISTA DI FILOSOFIA DEL DIRITTO-JOURNAL OF LEGAL PHILOSOPHY, 2019, 8 (01): : 107 - 124
  • [10] Big Data. New approaches of modelling and management
    Gil, David
    Song, Il-Yeol
    Aldana, Jose F.
    Trujillo, Juan
    [J]. COMPUTER STANDARDS & INTERFACES, 2017, 54 : 61 - 63