Seeing mobility: how software engineers produce unequal representations

ABSTRACT

Data produced by mobile networks are frequently presented as useful to understanding social phenomena related to human behavior. The risks associated with making use of massive datasets are often framed in terms of privacy, security, intellectual property, or liability. I show that the risks of mobile data sensing are not reducible to privacy, but are also related to how software engineers produce representations of individuals or populations. I characterize software engineering as a practice of producing abstractions and categorizations by articulating discursive and material elements. These may contribute to rendering certain groups of individuals invisible. If unaddressed, these risks can have consequences at least as serious as privacy violations.

KEYWORDS:

• Privacy
• big data
• massive data
• telecommunications data
• surveillance
• software engineers
• representation
• circulating reference

Acknowledgements

The author would like thank all the people behind this project, specially Markus Bylund and Eric Oluf Svee, who also helpfully commented and reviewed early drafts of the manuscript. He would also like to thank those who contributed with discussions and comments on early drafts of the analysis, especially Magnus Boman and Nina Wormbs. Finally, the author would like to thank those who reviewed and commented on final drafts of the manuscript in particular the anonymous reviewers of Engineering Studies, Kacey Beddoes, and especially Gary Downey, whose comments helped improve and clarify this manuscript. This research was partially funded by FCT (Fundação para a Ciência e a Tecnologia) with the grant SFRH/BD/60803/2009.

Notes

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