How I Learned to Stop Worrying and Love Big Data

How I Learned to Stop Worrying and Love Big Data

by beck haberstroh

A popular meme argues that “if we want the rewards of being loved we have to submit to the mortifying ordeal of being known.” These words were written by Tim Krieder in a New York Times essay where he reflected on the experience of being accidentally cc’d on an email from one friend to some other friends about his goats. Not everyone likes Tim’s goats! 

Krieder goes on to imagine that “the single most devastating cyberattack a diabolical and anarchic mind could design” would be simply to “make every email and text ever sent universally public.” If we could all see, as he did, what our friends and colleagues really say about us, “the fabric of society would instantly evaporate.” Civilization depends on our ability to gossip and whisper. Privacy is essential for social order. And yet, as he processes his discomfort, Krieder comes to the conclusion that building trust with others means acknowledging that they observe you in your strengths and flaws. We must reveal our imperfections if we want to form authentic, loving relationships. 

Today, in the United States, we are experiencing the flipside of Krieder’s stated fear: our digital life is being shared, not publicly, but with a complex web of private actors. Krieder’s essay was published in 2013, the same year that Edward Snowden leaked classified information from the National Security Administration (NSA) that revealed extensive government surveillance of American civilians. Recently, we are coming to terms with an audience that includes not just our government, but also private companies. In the TikTok hearings this month, members of Congress questioned the app’s chief executive about its Chinese owner, ByteDance, as well as its handling of U.S. user data. As Dell Cameron writes in Wired, these hearings did not reveal so much about TikTok as they did about “how desperately the United States needs national data-privacy protection.” These issues are not at all exclusive to TikTok, but extend to many, mostly American-owned companies. “Surveillance capitalism,” a term coined by Shoshana Zuboff in 2014, is one way to describe this commodification of our personal data. 

We are increasingly confronted with the various forces to which we must ‘submit’ in order to gain access to goods and services. Phones, apps, and websites might ask permission to collect your data. Stores might inform you that they are recording your image and purchases. Social media companies, websites, phone and computer producers, internet providers, and indeed insurance agencies, healthcare corporations, government offices, and others make the argument that we can only be properly cared for if we give them all of our information. Even our mental health data, as a 2023 study by Joanne Kim at Duke University revealed, is not safe from being sold by data brokers. By submitting to the mortifying ordeal of being known to a company, we are told, we will reap benefits. Without a doubt, many of us do.

The “rewards of being loved” are, of course, not distributed equitably. Imbalances of power are amplified by big data. The public relations ideal of this transaction promises ads for shockingly perfect dream products, as well as hilarious videos, insightful articles, and lucrative networking. Instead, the mass collection and exchange of our information has produced a reality that affects the cost and accessibility of insurance, housing, and healthcare, and empowers law enforcement and the carceral state. Algorithmic bias reaches deep into the folds of each of our daily lives, some examples of which are detailed in Safiya Noble’s 2018 book, Algorithms of Oppression and Cathy O’Neil’s 2016 book Weapons of Math Destruction. 

This ordeal is “mortifying,” in part, because we know that we are being watched and because it can feel like there is nothing, really, to do about it. The demands of our work, living conditions, or social relationships might make it difficult or impossible to negotiate the terms of our participation. Of course, many people can and must evade watchful eyes and there will always be those who, for reasons that include lack of resources, threat of violence, or personal politics and values, live their lives offline to varying degrees. The margins offer many alternative models—but most of us have chosen or are forced, consciously or not, to submit.

Sometimes I think about my actions across different devices and platforms as a kind of performance. Surveillance capitalism relies upon this performance being predictable. By behaving with consistency, I ensure that the models that are built about me are accurate and profitable. The routines of my daily life are translated into scripts. 

I’d like to rewrite some of the show.

Within performance art, a “score” is a short set of instructions for a performer to follow, taking its name from the idea of a musical score. Scores are a way to explore everyday objects and situations. My collaborator Katie Giritlian and I often use scores as a part of our process, and our first ‘collaboration’ was hosting a night with friends exploring these kinds of rapid, impromptu exercises. 

Scores can interrupt what is otherwise routine. While these interventions may be absurd, they may also give us insight into how our activities are transformed into data. Scores give us a way of understanding how a piece of a structure operates, or how we operate within it. Or, at the least, they can be fun. 

HOW TO USE THESE SCORES / GATHER YOUR SUPPLIES

These scores target the ways that our actions in digital spaces are used to build models of our behavior and are sold to data brokers. They are written to work across a wide variety of apps and devices—phones, laptops, search engines, social media platforms, messaging apps, and web browsing. The efficacy of these scores will likely be affected by what kinds of privacy restrictions you have set up on different devices, websites, and applications. Before you begin working with these scores, you may want to research and review, to the extent that you can, what data is being collected about you and how different applications have categorized you already.

Some of these scores can be ‘performed’ within moments, some require a deeper investment, and some act more as a poetic provocation. As you enact these micro performances, observe what happens to your feed, the kinds of ads that you get and content that you get served, and the ways that your data categorizations on different apps change. Remember that what you can see is only a small part of what is collected and sold about you.

A limitation of the approach offered in this syllabus is that it doesn’t take into account the different policies and protocols of each of these digital environments. Different companies reveal different elements of their data-collection methods and give users, each of us, different degrees of choice and insight. Some companies and governments work together and some do not. And all of this is constantly changing and most of it is a series of black boxes. Part of the problem is that the granular specifics of this ‘system’ are impossible to neatly summarize, even for an expert (which I am not). 

SCORES

Write your own! 

• Consider an aspect of your personal data that you would like to explore.
• Write a short score. Include action words. Give it a title.
• Email it to me, or, if you have an are.na account, add it to this shared are.na for all to enjoy.

REFLECTIONS

• How did it feel to (mis)use these digital spaces? 
• What, if anything, did you observe as a response to your scored performance? Did you notice any changes in the kind of ads you were served, content you were shown, or other functioning of these spaces?
• What did you learn about your existing habits within these different apps, platforms, and devices? What did it tell you about what kind of ‘user’ you are? In what ways is yourself as a ‘user’ an extension of yourself, and in what ways is it not?
• What did you learn about your values and beliefs? 
• Did any emotions arise through completing any of these scores? Curiosity, vulnerability, fear, anger, joy, shame?
• What questions do you have now?

RELATED READING, CITATION & IMPERFECT LINEAGE OF THESE IDEAS
A highly abbreviated, partial list of artists working with scores and issues of data privacy who inspire me and this syllabus especially:

• The Fluxus Movement and Yoko Ono’s Grapefruit
• Allan Kaprow’s Happenings
• The School for Poetic Computation
• The Surveillance Camera Players, who performed plays such as Waiting for Godot for CCTV cameras in New York City as a form of protest
• Kameelah Janan Rasheed, Scoring the Stacks, and other works
• Lai Yi Ohlsen, 100 scores: movement inspired by computers, and other works
• Max Fowler, Open Source Feeds, and other works
• Christine Sun Kim, Scores and Transcripts, and other works
• Nat Pyper, Ways of Looking, and other works
• Katie Giritlian, our “How to Draw the Horizon with a Friend,” her “Plays for the Waiting Camera” and Paper Cameras Press and the process of writing for it along with Mira Dayal
• Hasan Elahi, Thousand Little Brothers and related self-surveillance projects
• Data Cindy, Sherman Query workshop led by Melanie Hoff and Dan Taeyoung 
• A discussion led by Doreen A. Ríos at SOMA Summer 2022: Avatars in Paradise
• What is at stake? During her talk at the Vision and Technology conference in 2018, micha cárdenas argued that we should use our technologies with a consideration of those most vulnerable within our networks. It is not just ourselves that are imperiled through our data, but all those who we include in our community. cárdenas is a member of the Electronic Disturbance Theater, whose other members have included Brett Stalbaum, Stefan Wray, Carmin Karasic, Amy Sara Carroll, Elle Mehrmand, and Ricardo Dominguez, who advised my graduate thesis.

SPECIAL THANKS

To Julia and Gillian of the Syllabus Project, as well as Max, Katie, and my dad for thoughtfully reading and offering feedback on earlier drafts of this text.

beck’s syllabus references Katie Giritlian and Lai Yi Ohlsen, both of whom are Syllabus contributors.