www.ssoar.info Pattern Discrimination Apprich, Clemens; Chun, Wendy Hui Kyong; Cramer, Florian; Steyerl, Hito Veröffentlichungsversion / Published Version Sammelwerk / collection Empfohlene Zitierung / Suggested Citation: Apprich, C., Chun, W. H. K., Cramer, F., & Steyerl, H. (2018). Pattern Discrimination. (In Search of Media). Lüneburg: meson press. https://doi.org/10.14619/1457 Nutzungsbedingungen: Terms of use: Dieser Text wird unter einer CC BY-NC Lizenz (Namensnennung- This document is made available under a CC BY-NC Licence Nicht-kommerziell) zur Verfügung gestellt. Nähere Auskünfte zu (Attribution-NonCommercial). For more Information see: den CC-Lizenzen finden Sie hier: https://creativecommons.org/licenses/by-nc/4.0 https://creativecommons.org/licenses/by-nc/4.0/deed.de Apprich, Chun, Cramer, Steyerl Pattern Discrimination Pattern PATTERN DISCRIMINATION APPRICH CHUN CRAMER STEYERL Pattern Discrimination IN SEARCH OF MEDIA Götz Bachman, Timon Beyes, Mercedes Bunz, and Wendy Hui Kyong Chun, Series Editors Communication Machine Markets Pattern Discrimination Remain Pattern Discrimination Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl IN SEARCH OF MEDIA University of Minnesota Press Minneapolis London meson press In Search of Media is a joint collaboration between meson press and the University of Minnesota Press. Bibliographical Information of the German National Library The German National Library lists this publication in the Deutsche Nationalbibliografie (German National Bibliography); detailed bibliographic information is available online at portal.d-nb.de. Published in 2018 by meson press (Lüneburg, Germany ) in collaboration with the University of Minnesota Press (Minneapolis, USA). Design concept: Torsten Köchlin, Silke Krieg Cover image: Sascha Pohflepp ISBN (PDF): 978-3-95796-145-7 DOI: 10.14619/1457 The digital edition of this publication can be downloaded freely at: meson.press. The print edition is available from University of Minnesota Press at: www.upress.umn.edu. This Publication is licensed under CC-BY-NC-4.0 International. To view a copy of this license, visit: creativecommons.org/ licenses/by-nc/4.0/ Contents Series Foreword vii Introduction ix Clemens Apprich [ 1 ] A Sea of Data: Pattern Recognition and Corporate Animism (Forked Version) 1 Hito Steyerl [ 2 ] Crapularity Hermeneutics: Interpretation as the Blind Spot of Analytics, Artificial Intelligence, and Other Algorithmic Producers of the Postapocalyptic Present 23 Florian Cramer [ 3 ] Queerying Homophily 59 Wendy Hui Kyong Chun [ 4 ] Data Paranoia: How to Make Sense of Pattern Discrimination 99 Clemens Apprich Authors 123 Series Foreword “Media determine our situation,” Friedrich Kittler infamously wrote in his Introduction to Gramophone, Film, Typewriter. Although this dictum is certainly extreme— and media archaeology has been critiqued for being overly dramatic and focused on technological developments— it propels us to keep thinking about media as setting the terms for which we live, socialize, communicate, orga- nize, do scholarship, et cetera. After all, as Kittler continued in his opening statement almost thirty years ago, our situation, “in spite or because” of media, “deserves a description.” What, then, are the terms— the limits, the conditions, the periods, the relations, the phrases— of media? And, what is the relationship between these terms and determination? This book series, In Search of Media, answers these questions by investigating the often elliptical “terms of media” under which users operate. That is, rather than produce a series of explanatory keyword-based texts to describe media practices, the goal is to understand the conditions (the “terms”) under which media is produced, as well as the ways in which media impacts and changes these terms. Clearly, the rise of search engines has fostered the proliferation and predominance of keywords and terms. At the same time, it has changed the very nature of keywords, since now any word and pattern can become “key.” Even further, it has transformed the very process of learning, since search presumes that, (a) with the right phrase, any question can be answered and (b) that the answers lie within the database. The truth, in other words, is “in viii there.” The impact of search/media on knowledge, however, goes beyond search engines. Increasingly, disciplines—from sociology to economics, from the arts to literature— are in search of media as a way to revitalize their methods and objects of study. Our current media situation therefore seems to imply a new term, understood as temporal shifts of mediatic conditioning. Most broadly, then, this series asks: What are the terms or conditions of knowledge itself? To answer this question, each book features interventions by two (or more) authors, whose approach to a term—to begin with: communication, pattern discrimination, markets, remain, machine— diverge and converge in surprising ways. By pairing up scholars from North America and Europe, this series also advances media theory by obviating the proverbial “ten year gap” that exists across language barriers due to the vagaries of translation and local academic customs. The series aims to provoke new descriptions, prescriptions, and hypotheses—to rethink and reimagine what media can and must do. Introduction Clemens Apprich By now, the fact that social networks create “echo chambers” has become a truism. As we know from Greek mythology, Echo, the loquacious mountain nymph, was condemned to repeating phrases— as a punishment for helping Zeus hide his many affairs from Hera. Rejected by Narcissus, she wasted away until nothing but an echo remained. Narcissus in turn—as punishment for his many cruel rejections—fell in love with his own image and then killed himself, a victim of unrequited love. Hence, one may conclude, the inability to respond to others makes reciprocal exchange impossible and isolates the individual. In a narcissistic culture of self-affirmation, fostered by algorithmic personalization, communality— if not democracy— allegedly has been destroyed. But this analogy misses a deeper implication of the sociotechnical transformation. Concealed behind the “echo chambers” and “filter bubbles” of social media is an incredibly reductive identity politics, which posits class, race, and gender as “immutable” categories. Hence, at a time in which Western democracies have become “postracial” and vocal conservative and liberal-progressive critics within the humanities have declared studies of race/class/ gender/sexuality passé, identity has returned with a vengeance— that is, if it ever left. To understand the kinds of identity politics enabled by network technologies, this book examines a fundamental axiom of compu- tational cultures: pattern discrimination. While the word discrimi- nation originates from the Latin verb discriminare, where it simply x means “to separate, to distinguish, or to make a distinction,” it was in the late nineteenth century that it became overtly political. In parallel to the development of racist ideology, discrimination since then has referred to a prejudicial treatment of individuals based on a social category (e.g., race, gender, sexuality, age, class). However, in different terminologies the original meaning of the term has been preserved. This is why in computer science “pattern discrim- ination” is still used as a technical term to describe the imposition of identity on input data, in order to filter (i.e., to discriminate) information from it. But far from being a neutral process, the delineation and application of patterns is in itself a highly political issue, even if hidden behind a technical terminology. The point of this book is to trace and uncover the implicit ties between the ideo- logical and technical uses of discrimination, as we can experience it in algorithmically enhanced systems of pattern recognition. What would happen if we took discrimination with regard to data- driven politics seriously and built systems that acknowledged the fundamental fluidity of identity? What would happen if network science and Big Data met critical theory? In her essay, Hito Steyerl offers a taste of what this could mean. She shows us the hardwired ideologies of a machinic vision, in which data builds the basis of our reality. However, this reality doesn’t necessarily match with the catchphrases of the data industry. Rather than a smooth operation, algorithmically enhanced pattern recognition struggles with a massive amount of real— that is, dirty—data. As Steyerl explains, algorithms must constantly fix the mess that we call life. And just like in real life, the criteria to decide what to include and exclude are intrinsically political. But then why is it that there is almost no discussion about the implicit racist, sexist, and classist assumptions within network analytics? How, in other words, can we have a serious debate about Big Data and pattern discrimination if most people (or their data) are either blanked or don’t really care? This is the question Florian Cramer tackles in his text by contrasting computer analytics with classical hermeneutics. Instead of a narrative function based on syntax, computers employ statistical methods, thereby leaving behind older concepts of critical inter- xi pretation. But since data is never pure and analytics never fully objective, interpretation— and thus hermeneutics— recurs through the back door of computational analytics. In this sense, allegedly “old” concepts of the humanities may give