How dating apps exploit India’s loosely formed definition of ‘personal information’
In ‘What Privacy Means’, Siddharth Sonkar explains how an Indian citizen’s privacy is hardly ‘private’.
W hen Judith Duportail, a freelance journalist, broke up with her boyfriend, she downloaded Tinder, the dating app. She began getting addicted to the app and in the course of using it, being a journalist, she became curious about how the app was helping her find matches. With the help of privacy activist Paul-Olivier Dehaye – the founder of Personal Data.IO, which aims to ensure data protection rights – she sent an email to Tinder asking it to show all the data it had on her.
How dating apps exploit India’s loosely formed definition of ‘personal information’
Soon, she was surprised when she received 800 pages of information – about her Facebook likes, links to her old Instagram pictures, ranking of the age group of men she was interested in, the number of friends she had on Facebook and where she had carried out each and every online conversation with her matches. She decided to write a book to describe her experience when exploring herself through Tinder called L’Amour sous algorithme (Love Under Algorithm). During this exploration, Duportail discovered that Tinder uses a desirability rank known as the ‘Elo Score’. To put it simply, the application ranks every profile to assess who is a better match for someone. Duportail’s book reveals that Tinder uses a matching process system and method patent, as it encourages dates between users with similar profiles. This system is capable of classifying users in relation to their intelligence, preferences, wealth, ethnicity, and attractiveness. Reportedly, Tinder rejected Duportail’s claims that it uses this patent, citing that this part of its application was irrelevant to the operability of its platform.
‘We don’t believe in stereotypes,’ said Tinder. However, according to Duportail, the story is quite different, pointing out that Tinder collects information that is far more than what we ordinarily expect while using an app. It knows how long we use the application, what our age filters are, what ages we typically match with, who we wish to match with, every message that we send, where and when we sent it, and even our current job. Further, when we link our Tinder to other applications such as Facebook, Instagram or Spotify, a lot more information about us can be accessed. Then, Tinder even knows which posts we may have liked.
Alessandro Acquisti, professor at Carnegie Mellon University, describes this as ‘secondary implicit disclosed information’ which becomes obvious by observing our behaviour on the application, which is able to tell what is the percentage of black men, white men or Asians that one may match with, what are the types of people that may be interested in us, what words we use and how much time we spend on someone else’s profile before swiping right or left. When asked why Tinder needs so much data about us, a spokesperson said that it aimed ‘…to personalize the experience for each of the users around the world’. By having more data, according to the spokesperson, they are able to personalize all of our browsing experiences on Tinder. However, when Tinder was asked what kind of profiles we would be shown based on this personalization (that is, what is the logic behind profiling our matches?), the spokesperson said, ‘Our matching tools are a core part of our technology and intellectual property, and we are ultimately unable to share information about [our] proprietary tools.’
According to Paul-Olivier Dehaye, the privacy activist communicating with Tinder on Judith’s behalf, this information is not just used by Tinder to observe our behaviour and shape the choices we make in our ÑasualDates ekÅŸi quest for love. The data is shared to further affect the jobs we are offered on LinkedIn, or to determine how much we may be willing to pay while insuring a car, or which ad we may want to see online or whether we can subscribe to a particular loan.
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