Algorithmic Autobiographies and Fictions
How to Write with Your Digital Self
By Sophie Bishop (King’s College London) and Tanya Kant (University of Sussex)
In August 2020, Netflix released The Social Dilemma, a “drama-documentary” about the harms engendered by social media platforms, featuring talking heads of former engineers and executives. The film was widely panned for sensationalizing the addictive qualities of technology and sidelining the greater harms it sustains to marginalized peoples. Despite this, audience responses to the film reveal a deep public interest and collective concern regarding social media’s power in the daily lives of users.
Our research workshop, “Algorithmic Autobiographies and Fictions,” is animated by the point that “everyday folks” are just as interested in how algorithms shape our world as those who study them academically and professionally. In this blog post, we provide an outline for researchers who want to run our practical workshops to understand how audiences conceive of their personal relationships with their data. The design of our workshop is informed by both of our research, which acknowledges that individuals develop theories and strategies to help them navigate these technologies, even when they are ostensibly “black boxed.” Sophie’s work looks at how influencers’ community conversation and gossip about platforms shapes the content that they produce and distribute. Tanya’s examines how the anticipation and perception of advertising personalization shapes users’ sense of selves. We want to understand how users think these processes draw from their identities, and in turn, shape them.
…these relaxed and generative workshops prioritize creative engagement with data.
Titled “Algorithmic biographies and fictions,” these relaxed and generative workshops prioritize creative engagement with data. As we tell our participants, this is a “no tech workshop”—no experience with data is required. Instead, we use creative writing and drawing techniques to allow social media users to “meet and greet”’ their “algorithmic selves” through the ad preference profiles that social media platforms create about their users. The workshops have a pedagogical function: we use them as an opportunity to increase data and algorithmic literacies, forms of digital literacy that Henderson et al. note is currently in need of promotion with the wider public. Mostly though, we steer participants away from doom-laden prophesies of social breakdown and civil war. We hope instead that the workshop allows for dynamic engagement with social media data through creative writing and drawing in ways that increase user understanding and agency.
We hope instead that the workshop allows for dynamic engagement with social media data through creative writing and drawing in ways that increase user understanding and agency.
We have run these workshops in a variety of settings, including to bleary-eyed revellers on a Saturday morning at a popular music festival, in undergraduate/postgraduate modules from both our universities, and to colleagues at critical media studies conferences. We find that the workshop works well with all these audiences; it lends itself particularly well to teaching, especially during classes on platformization, ad targeting, and data privacy. Prior to COVID-19, we ran these workshops in-person; but in the wake of the pandemic were pleased to find that they also work well on Zoom, as long as sessions are synchronous.
The workshops inform a wider project we are undertaking on “Demystifying data profiling.” We are collating and analyzing the writings and drawings produced by workshop participants (having received ethical approval from our universities), to understand how creative engagement can be used to improve algorithmic literacy, and how participants can represent their algorithmic selves through artistic engagement. The workshops we have run so far suggest some indicative findings. Firstly, social media users predominantly find their own digital profiles to be erroneous, absurd, and caricaturistic — users’ data profiles do not fit with their own understanding of their selves. Secondly, creative writing and drawing can be used as educational and engaging tools to promote algorithmic literacy in social media audiences. This fits into a wider third finding: the project has so far found that drawings/writings of participants challenge popular understandings of data as scientific in ways that help to reveal profiling as sometimes crude and erroneous; a crudity that, as the workshops stress, still presents a myriad of social cultural issues for those profiled.
How to Run the Workshop
Workshops take around 1.5 to 2 hours to run. In non-COVID times, they work best with 20 to 30 participants and in a space where participants can sit around tables, writing and drawing together. The format also lends itself well to video conferences online for both small and larger groups. Numbers can be set based on the level of interaction desired. For the creative tasks, participants just need access to pens, paper, and their social media profiles—the more creative materials the better, depending on what budget allows! During larger workshops, organizers may not have time to hear from all participants, but conversation can be ongoing on Twitter and other secondary platforms.
We begin each workshop by giving a basic overview of various types of social media tracking, including a guide to ad profiling and cookies, and why we should care about them. Organizers can piece the overview together based on their own research interests and priorities. We cover topics such as cookies functionality, privacy, and data sharing. We then show participants examples of our own ad preference profiles (Facebook identifies Tanya’s passion for toilets, feminism, and cattle). We exhibit our own pictures and writing (Tanya, on the toilet, feminist sign and cattle), acknowledging that, as workshop leaders, it is important for us to reflect on our own ambivalence engendered by our data. Sharing can feel oddly personal, even when we accept the “wrongness” of our digital identities.
Next up, we give step-by-step instructions on how to access available ad preferences on various social media platforms. Using handouts, we usually show participants how to access their ad preferences on Google, Facebook, or Instagram. The pathways for accessing this information are adjusted regularly by platforms, so it’s important to revisit the instructions we give out prior to each workshop. If time allows, we invite participants to access their data for each social media and cross-check their results.
After asking participants to access their ad preference profiles on the platform of their choice, we ask them to jot down some notes about what “interest categories” stand out for them: if they have lots or little listed interests, how they feel about what has been inferred about them, and how this will affect what they draw/write. We then move on to the first exercise: drawing your “algorithmic self.” Promoted by questions such as “What do they look like? What is their age and gender, if any?”, we ask participants to draw a picture. We stress that no artistic skill is required and that their “algorithmic selves” will most likely reflect only a fraction of their listed interests: there are usually too many to encompass them all in one picture (an important pedagogical point on data tracking in and of itself).
We then move on to the creative writing exercise: Sophie leads with a list of her ad preferences from Instagram, writing a short story that she reads as an example. We then ask participants to write a short story, poem, or play (or any format of writing they like) describing a “day out” with their digital self. Prompted by questions such as “What did you ask your algorithmic self? What did they say to you? What did they want to do?”, we ask participants to write for around 15 minutes.
Participants then share their writing and drawing with the group; this often leads to the discussion returning back to the themes outlined in the workshop introduction. We conclude with a short set of guidelines on how to change (or control) ad settings, giving advice on tracker blockers and other tools that might help users enjoy more agency around their data profiles.
Sophie Bishop is a Lecturer at King’s College London in Digital Marketing and Communications. Her research looks at the feminist political economy of creative content production contingent to social media platforms.
Tanya Kant is a Lecturer in Media and Cultural Studies (Digital Media) at the University of Sussex. Her research explores algorithmic identity practice and everyday life, gender-targeted advertising, bots, and digital public service broadcasting.
