Big Data: A Normal Accident Waiting to Happen?
Widespread commercial use of the internet has significantly increased the volume and scope of data being collected by organisations. ‘Big data’ has emerged as a term to encapsulate both the technical and commercial aspects of this growing data collection activity. To date, much of the discussion of...
| Authors: | ; |
|---|---|
| Tipo de documento: | Recurso Electrónico Artigo |
| Idioma: | Inglês |
| Verificar disponibilidade: | HBZ Gateway |
| Interlibrary Loan: | Interlibrary Loan for the Fachinformationsdienste (Specialized Information Services in Germany) |
| Publicado em: |
2017
|
| Em: |
Journal of business ethics
Ano: 2017, Volume: 145, Número: 3, Páginas: 481-491 |
| Outras palavras-chave: | B
Normal accident theory
B Privacy B System accidents B Dados de massa |
| Acesso em linha: |
Volltext (JSTOR) Volltext (lizenzpflichtig) |
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| 520 | |a Widespread commercial use of the internet has significantly increased the volume and scope of data being collected by organisations. ‘Big data’ has emerged as a term to encapsulate both the technical and commercial aspects of this growing data collection activity. To date, much of the discussion of big data has centred upon its transformational potential for innovation and efficiency, yet there has been less reflection on its wider implications beyond commercial value creation. This paper builds upon normal accident theory (NAT) to analyse the broader ethical implications of big data. It argues that the strategies behind big data require organisational systems that leave them vulnerable to normal accidents, that is to say some form of accident or disaster that is both unanticipated and inevitable. Whilst NAT has previously focused on the consequences of physical accidents, this paper suggests a new form of system accident that we label data accidents. These have distinct, less tangible and more complex characteristics and raise significant questions over the role of individual privacy in a ‘data society’. The paper concludes by considering the ways in which the risks of such data accidents might be managed or mitigated. | ||
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