Download first, privacy later: Exploring the exchange of smartphone usage data for access to app-based services in India.

Abstract

This thesis reviewed scholarship in the field of media and cultural studies with specific focus on audience studies. Literature review was focused on key themes such as data practices and experiences, data privacy, advertising surveillance and issues around informed consent by users of digital platforms. The review identified a gap in research about user understanding of data exchange with digital platforms and experiences with personalised advertising in India. A mix of qualitative research methods were used to evaluate contemporary experiences of participants engaging with their personal data. This research explored the process of converting digital data trail into customised advertising for smartphone owners and their incentives to participate in this exchange of data for access to app-based services. Industry Experts working in media agencies and marketing function of advertisers were interviewed to understand various sources of digital data that are used for creating affinity audiences. Owners of smartphones in Mumbai and Delhi reflected on their awareness of automated data collection, trust threshold for sharing sensitive data and understanding of advertising technology. Participants discussed the affirmative nature of digital platforms and described services that were critical to their day-to-day functioning. Participants had a gradation of trust and all the apps needed to clear thresholds to be considered reliable. Most of the popular digital platforms were highly trusted on data safety. Digital platforms that scored high on trust quotient were also believed to obfuscate relevant information about the usage and storage of their data in lengthy terms and conditions. Four main reasons stated for not investing time to understand the use of software as service contracts were, There Is No Control (TINC), Fear of Missing (FOMO) on popular apps, there is no time (TINT) to read the lengthy terms and conditions and there is no option (TINO) as there was no alternative to the apps. Participants outlined multiple instances where they saw advertising about topics that they had recently discussed in the vicinity of their smartphones. This led to a widespread belief that smartphone apps such as Facebook and Instagram were listening to their conversations. Industry participants were able to describe an extensive array of practices that were used to identify the right target audience for their campaign, using algorithms running on large databases built on behavioural and transactional data. These processes created highly accurate predictive abilities that enabled highly accurate profiling of Internet users. Some Everyday Users were aware of these processes and the analysis identified them as algorithm-aware. Others were not equipped or motivated to discover information to understand advertising technology. In the absence of this information, participants used heuristics to understand the ability of digital platforms to deliver advertising that is so relevant to their current personal situation. This common-sense explanation for personalised advertising (Ads are listening to me) is named Folk Theory of Customised Advertising. The research highlights the enabling nature of digital technologies in India and outlines a requirement for an easy-to-use toolkit for everyday smartphone users to become algorithm-aware and privacy conscious.

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ORCID for Daniel Ashton: orcid.org/0000-0002-3120-1783

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