Mobile phones: privacy 02.04.12

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Mobile phones appear to offer independence and privacy, but in reality we are more exposed than ever before, says Jay Owens

Your mobile phone leaks. Behind the user interface, out of immediate view, it is sharing a lot more data than most people realise.

Take location. In exchange for offering Google Maps as a free service, Google is able to know where your phone is at all times. Your home and work addresses are easy to identify (your habitual locations at 3am and 10am respectively). These can be cross-referenced against Mosaic (market research company Experian's consumer classification) or Zoopla house price records to transform location into income and demographic data, allowing users to be sold as micro-targeted "market segments" of high-value to advertisers.

Mobile web surfing habits provide another stream of data. Mobile operators direct web traffic through their servers to manage network performance, but this also allows them to monitor the websites people visit. Monitoring web history provides data that is highly commercially exploitable.

Information storage is increasingly cheap and data protection laws are some distance behind the technology, meaning companies are building large datasets now to hedge against future restrictions.

Less legitimately, mobile phones can easily be compromised by malware and spyware. Apps may ask for greater rights than they need, allowing remote access to the phone's microphone and camera, text (such as emails or passwords) and location data. Occupy London protestors have been known to remove batteries and keep mobiles in a separate room while meeting to plan future actions. This may seem paranoid, but the Mark Kennedy case has shown that police infiltration of "domestic extremist" groups is common. Does mobile data sharing matter? Some would argue not: users are knowingly exchanging their data for free access to services. But the impact of such bargains goes beyond the individual. Companies such as insurers and financial lenders are keen to use whatever data they can to minimise risk. This may mean denying insurance or a mortgage on factors outside the applicant's control – simply on the likelihood that "people like you" (by location or web use) are more likely to default on payments.

The customised advertising enabled by mobile data also has costs. By being delivered on the basis of aggregated and probabilistic data, the recommendations made are normative. Does the working class teenager see ads for jobs in McDonalds rather than universities? Is pregnancy advice limited by religious affiliation? Personalised services offer convenience at the price of potentially constraining possibilities.

Behind the commercial value of mobile data is network analysis: modelling our social relationships (call histories, social media friends) and analysing patterns. This has substantial predictive capacities: where one user is unknown to a mobile operator, many personal details can be inferred from their patterns of interaction with known entities.

Social media analysts do not only focus on the "social graph" of relationships between people – they analyse "interest graphs" (relationships between topics of discussion such as music and technology) in the same way. To what extent does "the individual" remain the primary unit within these assemblages of behavioural data, social, material and semiotic relationships?

Jay Owens is a social media analyst at FACE, the research and innovation agency



Andy Gilmore



Jay Owens

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