Big Data: potentially discriminatory factors in data analysis

Authors

  • Caio Saraiva Coneglian UNESP - Universidade Estadual Paulista
  • José Eduardo Santarem Segundo USP - Universidade de São Paulo
  • Ricardo Cesar Gonçalves Sant'ana UNESP - Universidade Estadual Paulista

DOI:

https://doi.org/10.19132/1808-5245231.62-86

Keywords:

Big data. Data analysis. Discrimination. Potentially discriminatory factors.

Abstract

The experienced technological changes from the turn of the century caused a revolution in the Big Data society, in which the data analysis to determine patterns and behaviors could use large amounts of data. It is possible to notice that some analyses in the context of the Big Data are being conducted to generate discriminatory results. This study aims to identify factors that can potentially lead to discrimination in the process of data analysis. The methodology used was qualitative, exploratory and bibliographical, enumerating the discrimination cases. As the result, we identified possibly discriminatory factors and we provided an explanation of these factors. Through research, we noticed the need of showing deep reflection about the results that are obtained from the data analysis and the need of Information Science approaching such questions, in order to point out the paths to be taken.

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Author Biographies

Caio Saraiva Coneglian, UNESP - Universidade Estadual Paulista

Mestrando em Ciência da Informação no Programa de Pós Graduação em Ciência da Informação UNESP - Universidade Estadual Paulista. Graduado em Ciência da Computação pelo Centro Universitário Eurípides de Marília - UNIVEM.

José Eduardo Santarem Segundo, USP - Universidade de São Paulo

Doutor em Ciência da Informação na UNESP - Universidade Estadual Paulista. Docente da Universidade de São Paulo - USP. Professor vinculado ao Programa de Pós Gradução em Ciência da Informação da UNESP.

Ricardo Cesar Gonçalves Sant'ana, UNESP - Universidade Estadual Paulista

Doutor em Ciência da Informação na UNESP - Universidade Estadual Paulista. Docente da Universidade Estadual Paulista - UNESP. Professor vinculado ao Programa de Pós Gradução em Ciência da Informação da UNESP.

References

BAROCAS, Solon; SELBST, Andrew D. Big Data's Disparate Impact. Cali-fornia Law Review, Berkeley, v. 104, p. 671-732, 2016. Disponível em: <http://www.californialawreview.org/wp-content/uploads/2016/06/2Barocas-Selbst.pdf > Acesso em: 20 out. 2015.

BOURDIEU, Pierre. O poder simbólico. Lisboa: DIFEL; Rio De Janeiro: Ber-trand Brasil, 1989.

BUTLER, Declan. When Google got flu wrong. Nature, London, v. 494, n. 7436, p. 155-156, Feb. 2013. Disponível em: <http://www.nature.com/news/when-google-got-flu-wrong-1.12413> Acesso em: 26 jan. 2016.

CASADY, Tom. Police Legitimacy and Predictive Policing. Geography & Public Safety, Washington, v. 2. n. 4, p.1-16, mar. 2011. Disponível em: <http://www.nij.gov/topics/technology/maps/Documents/gps-bulletin-v2i4.pdf?Redirected=true>. Acesso em: 27 nov. 2015.

CHOW-WHITE, Peter A.; GREEN JR., Sandy E. Data Mining Difference in the Age of Big Data: Communication and the social shaping of genome technol-ogies from 1998 to 2007. International Journal of Communication, Los Ange-les, v. 7, p. 556-583, 2013. Disponível em: <http://ijoc.org/index.php/ijoc/article/view/1459/869>. Acesso em: 22 set. 2016.

CRAWFORD, Kate. Think again: big data. Foreign Policy, Washington, v. 9, 2013. Disponível em: <http://www.foreignpolicy.com/articles/2013/05/09/think_again_big_data>. Acesso em: 26 jan. 2016.

CROLL, Alistair. Big data is our generation’s civil rights issue, and we don’t know it. Big data now, Atlanta, p. 55-59, 2012. Disponível em: <http://solveforinteresting.com/big-data-is-our-generations-civil-rights-issue-and-we-dont-know-it/>. Acesso em: 26 jan. 2016.

DISCRIMINAÇÃO. In: DICIONÁRIO Priberam da Língua Portuguesa. Lis-boa: Priberam Informática, 2011. Disponível em: <http://www.priberam.pt/DLPO/discriminação>. Acesso em: 22 set. 2016.

FRANK, Morgan R. et al. Happiness and the patterns of life: A study of geolo-cated tweets. Scientific reports, London, v. 3, Set. 2013. Disponível em: <http://www.nature.com/articles/srep02625?WT.ec_id=SREP-20130917?message-global=remove&WT.ec_id=SREP-20130917> Acesso em: 26 jan. 2016.

GOLDSTEIN, Benjamin A.; WINKELMAYER, Wolfgang C. Comparative health services research across populations: the unused opportunities in big data. Kidney International, Bruxelas, v. 87, n. 6, p. 1094-1096, Jun. 2015.

GORDON, Charly. Big Data exclusions and disparate impact: investigating the exclusionary dynamics of the Big Data phenomenon. 2015. 37 f. Dissertação (Mestrado em Mídia, Comunicação e Desenvolvimento) - London School of Economics and Political Science, Londres. 2015. Disponível em: <http://www.lse.ac.uk/media@lse/research/mediaWorkingPapers/MScDissertationSeries/2014/Charly-Gordon-MSc-Dissertation-Series-AF.pdf>. Acesso em: 19 jul. 2016.

KAKHANI, Manish Kumar; KAKHANI, Sweeti; BIRADAR, S. R. Research Issues in Big Data Analytics. International Journal of Application or Innova-tion in Engineering & Management, Etmadpur, v. 2, n. 8, Aug. 2013. Disponí-vel em: <http://www.ijaiem.org/volume2issue8/IJAIEM-2013-08-29-070.pdf>. Acesso em: 22 set. 2016.

LERMAN, Jonas. Big data and its exclusions. Stanford law review online, Stanford, v. 66, Sep. 2013. Disponível em: <https://www.stanfordlawreview.org/online/privacy-and-big-data-big-data-and-its-exclusions/>. Acesso em: 22 set. 2016.

LOHR, Steve. Big data, trying to build better workers. The New York Times, New York, Apr. 21th 2013. Tecnologia, p. 4. Disponível em: <http://www.nytimes.com/2013/04/21/technology/big-data-trying-to-build-better-workers.html> Acesso em: 26 jan. 2016.

MAYER-SCHÖNBERGER, Viktor; CUKIER, Kenneth. Big data: A revolu-tion that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt, 2013.

MCAFEE, Andrew; BRYNJOLFSSON, Erik. Big Data: the management revo-lution. Harvard Business Review, Brighton, v. 90, n. 10, p. 61-67, oct. 2012. Disponível em: <https://hbr.org/2012/10/big-data-the-management-revolution#>. Acesso em: 22 set. 2016.

PERLROTH, Nicole. Fake twitter followers become multimillion-dollar busi-ness. The New York Times, Nova Iorque, 5 Abr. 2013. Bits. Disponível em: <http://bits.blogs.nytimes.com/2013/04/05/fake-twitter-followers-becomes-multimillion-dollar-business/?_r=0>. Acesso em: 25 nov. 2015.

PEW RESEARCH CENTER. Social Networking Fact Sheet. Washington, Pew Research Center, 2014. Disponível em: <http://www.pewinternet.org/fact-sheets/social-networking-fact-sheet/> Acesso em: 25 nov. 2015.

SANTANA, Ricardo Cesar Gonçalves. Ciclo de vida dos dados e o papel da Ciência da Informação. In: ENCONTRO NACIONAL DE PESQUISA EM CIÊNCIA DA INFORMAÇÃO, 15, Florianópolis, SC, 2013. Anais eletrônicos... Florianópolis, SC: ANCIB, 2013. Disponível em <http://enancib2013.ufsc.br/index.php/enancib2013/XIVenancib/paper/view/284/319> Acesso em: 2 fev. 2016.

STREET BUMP. About street bump. Boston, 2015. Disponível em: <http://www.streetbump.org/about>. Acesso em: 27 nov. 2015.

SWEENEY, Latanya. Discrimination in online ad delivery. Ad Delivery, Nova Iorque, v. 11, n. 3, p. 1-19, Apr. 2013. Disponível em: <http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2208240>. Acesso em: 22 set. 2016.

TAURION, Cezar. Big data. Rio de Janeiro: Brasport, 2013.

VALZ, Duane R. Dynamic pricing models for digital content. US 20080154798 A1. 26 jun. 2008. Disponível em: <http://www.google.com/patents/US20080154798>. Acesso em: 27 nov. 2015.

ZIKOPOULOS, Paul et al. Understanding big data: Analytics for enterprise class hadoop and streaming data. New York: McGraw-Hill, 2011. Disponível em: <http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=WH&infotype=SA&appname=SWGE_IM_DD_USEN&htmlfid=IML14297USEN&attachment=IML14297USEN.PDF>. Acesso em: 22 set. 2016.

Published

2017-01-01

How to Cite

CONEGLIAN, Caio Saraiva; SANTAREM SEGUNDO, José Eduardo; SANT’ANA, Ricardo Cesar Gonçalves. Big Data: potentially discriminatory factors in data analysis. Em Questão, Porto Alegre, v. 23, n. 1, p. 62–86, 2017. DOI: 10.19132/1808-5245231.62-86. Disponível em: https://seer.ufrgs.br/index.php/EmQuestao/article/view/62122. Acesso em: 3 aug. 2026.

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