Ambient Intimacy and the Habituation of Software Updates – Amelia Acker
Ambient intimacy and the habituation of software updates
In May of 2015, Tinder updated to version 4.4. One of the new characteristics of the update was to expand the “common friends” feature by using more data from users’ social network graph from their Facebook profiles. As a result, users immediately began to see more exes of friends appearing in their Tinder streams. I started to research the effects of the update and learned that the new 4.4 update led to a variety of reactions—mostly poor, ranging from departing the app, cross-channel PSAs not to update the app, even new habits or rules about swiping right or left to avoid bots. The new update that pushed an extra degree of connectivity from users’ social network graph (the profiles of friends of Facebook friends) was unusual because it mistook the data about closeness in a social network for potential intimacy. For example, most people were unsettled, even freaked out, by being pushed towards an ex’s ex (or for some that I interviewed, an ex’s newest Facebook friend that they had just met on Tinder). My research also found that updating mobile dating software itself has become a habit of intimacy that points to the relationships we have to our devices, and the ways we connect with these tools, and how we understand the potentiality to connect to others in networks, virtual or otherwise.
Should it surprise us that mobile software updates increasingly govern our intimate relationships in new, and sometimes uncomfortable ways? Our phones not only represent ourselves, but they are always-already connected to 3G and 4G mobile networks that connect us to the Internet and social network platforms like Facebook, Instagram, Tinder and Scruff. These platforms collect data about our location, tastes, and personal connections to make the tools we use more precise and tailored to our needs. My point here is that, as the world reaches near complete mobile device penetration, our contemporary lives are now constantly connected to digital networks. And as we use these platforms to create and access data to solve problems like finding a date, creating and accessing user data with software has become a new form of belonging. I am especially interested in the sociotechnical practices surrounding mobile software updates and in the constant re-engineering of social media platforms, data standards, apps, and wireless network architectures that marks this moment. Each of these create a layered assemblage, what Benjamin Bratton might call a “meta-infrastructure” that is forming the base of new kinds of data cultures. We are beginning to see, as Karen Levy has shown in her work on surveillance, the datafication of intimacy. Increasingly, the quantification of intimacy is part of this constant churn of making and remaking ourselves with data in wireless networks, including the ways we are becoming habituated into updating software for our apps. We update software, devices, terms of service, and privacy agreements at a breakneck pace as part of networked living, these updates then govern how user data is then folded into systems, and enrolled through updates and then how these data, collected, or dispersed or assembled into an ecology of software applications that we use every day.
As part of this research, I’ve been trying to is to think of updating mobile software like the Tinder app as an artifact of habit. Thinking of updates as habits allows me study what they mean to different groups of people that use mobile software almost daily, and in turn, tends to be updated by developers often. This steady back and forth of updating and change tells us about our habits as networked communities, and further how we make sense of how our user data as we create it, especially in those moments where using apps and creating data spills across platforms and entangles communities, individuals, and new relationships with competing views of networked technology and its purposes. The idea of understanding updates as a process of habituation is not new, and it’s not necessarily new to approaches for understanding digital technology either. In fact, “updating to the new” is part of our consumption culture: we buy skinny jeans, new headphones, update our hair styles. However, software updates, particularly those everyday software applications, such as iTunes or Microsoft Word or mobile apps like Instagram or Tinder, are updated frequently (by users and developers), and as forms of habits, they are more slippery and hard to tie down. The interesting thing about habits is that they creep, and it’s really hard to point at a particular moment and say, “this is when the habit was born, here is its point of origin or conception point.” If creating data as users is a new form of belonging, then the habituation of updating these forms of data collection, creation and access becomes a site for their study, interpretation and critique.
Scholars who have studied the nature of habits like Clare Carlisle or Wendy Chun, comment on two aspects. First, is the forward operating logic of habits that makes them hard to locate and then apprehend. Because they may be boring to think about, there may not be much of an incentive to evaluate or resist their conventional repetition (unless they’re bad, in which case we tend to create traditions and practices around “breaking them”). The second idea is that habit can influence the distinct character of individuals and that when we share habits together in concert, we make communities and it is the shared conventions of habits that bring people together. That is, we understand ourselves and who we are and how we belong together by the habits we take up, the habits that we resist, the habits we break, and even the new habits we create.
For those data traces that influence and quantify intimacy, the documentation and empirical evidence of habituation not only reveals users’ contributions to software but also how users understand themselves in software creation and algorithms as they try and connect with people. In my Tinder interviews, people often reacted to social network graph updates with anticipation, one said, “It’s as if I’m always on tenterhooks.” The expression, tenterhook, comes from the Latin word tendere, to stretch—when people use the phrase it means they are stretched with anxiety; the tenterhook is this device which stretches tents, wool, or leather hides. One of the things that helps us locate the habituation of software updates is moments when we come to experience a rupture in the “ambient intimacy” of networks, the moments when we are on tenterhooks (perhaps what we should call then tinderhooks), when we suddenly realize that this waiting, this stretching, this anxiety, is actually painful but also how the tool works, how data is collected and learns our preferences. An update may hurt, or cause anxiety, or perhaps the unease is dispersed over little moments, but suddenly when we become used to it, the habit is becoming. It is being formed. Hence access to the location data and social graph data does more, I argue, than simply change the way the app works or how the algorithm is experienced by users. It changes the ways in which users move through space and their communities. Tinder users are then typified as negotiating those constraints with such user data, data about their collective dating community in particular.
We have created an ambient intimacy built up and created around the habits of updating software. What do software studies such as these findings add to contemporary understandings of intimacy? Updates often elide the kinds of open and closed data that are being collected about users, but also being accessed by users through software apps and algorithms. Understanding the dimensions of user data collected as part of the social network graph provides good context for analyzing the political, economic, and broader cultural impact of accessing geographic, personal, intimate, social network data with mobile platforms. There is a kind of booming silence around the depoliticization of user data in popular rhetoric of big data and the capacious frontierism of data science. To live with this idea of unlimited and ongoing data collection is to accept, consciously or unconsciously, a deeply mechanistic view of human behavior. There is already some literature about this impact of datafication, by way of what my friend and collaborator Brian Beaton has called data criticism. We are quickly becoming new kinds of data subjects with habituated software updates. This subjectivity is supported by networked infrastructures as a result of constant creation and collection of data, and metadata applications. If habit underlies the distinct character of every individual, and shared habits bring people together into communities—experts, parents, students, we have yet to attend critically to trace data that looks to become a large portion of the human cultural record. Here I have argued that the historical ontology these user data traces deserves more attention, especially as it relates to new forms of ambient intimacy and the production of invisibility through new habits. We need a data criticism that not only gives us new understandings of intimacy and personal connection, but new tools for critically examining and apprehending the software in our lives.
Acker, A., & Beaton, B. (2016, January). Software Update Unrest: The Recent Happenings Around Tinder and Tesla. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 1891-1900). IEEE.
Beaton, B. (2016). How to Respond to Data Science: Early Data Criticism by Lionel Trilling. Information & Culture, 51(3), 352-372.
Bratton, B. H. (2016). The stack: On software and sovereignty. MIT Press.
Carlisle, C. (2014). On habit: Thinking in action. Abingdon, UK: Routledge.
Chun, W. H. K. (2016). Updating to Remain the Same: Habitual New Media. MIT Press.
Levy, K. E. (2014). Intimate Surveillance. Idaho Law Review, 51, 679-693.
Amelia Acker studies the emergence and standardization of new information objects and data traces communication networks. Currently, she is researching data cultures, information infrastructures and digital preservation contexts that support long term cultural memory and literacy. Amelia’s current research program addresses emerging digital traces and mobile computing cultures that are shaped by new data collection practices amongst different kinds of users, designers, technologists, and institutions. http://ameliaacker.com/