Wendy Hui Kyong Chun

Creating communities of care in the digital world Data Fluencies offers a model for enacting theories of data justice, methods of community engagement, and practical approaches to disrupting institutions and infrastructures that have diminished the capacities of everyday digital technology users. Combining humanities-based critical thinking, computational data analyses, arts-based research cocreation, and media making, data fluencies offer creative and imaginative approaches to investigating and countering algorithmic discrimination, digital surveillance, mis- and disinformation, and deep fake versions of reality. Not fixed or static, data fluencies move with, through, and against data streams to build the worlds we want, not the ones algorithms push on us. Presenting real-world examples, the authors demonstrate how data fluencies transcend difference and counter the proliferation of hate and toxicity online. As they outline visions for disrupting the past to reimagine the future, the authors guide the way in devising new ways to think, act, and imagine – to influence and reshape the currents that flow through our data-driven world. Distributed for meson press. Retail e-book files for this title are screen-reader friendly with images accompanied by short alt text and/or extended descriptions.

How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U. S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.

What makes information feel true or compelling in our contemporary digital societies? This book brings together different disciplinary understandings of "authenticity" in order to find alternative ways to approach mis- and disinformation that go beyond contemporary fact-checking and its search for the "authentic" truth. Patterned under the algorithmic flows of digital capitalism, authenticity itself is subject to variation, iteration, and outside influence. Linking cross-disciplinary research on the history and practices of algorithmic authenticity points to new research questions to understand the impact of algorithmic authenticity on social life and its role in contemporary information disorder.

How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? To answer this question, this book investigates a fundamental axiom in computer science: pattern discrimination. By imposing identity on input data, in order to filter-that is, to discriminate-signals from noise, patterns become a highly political issue. Algorithmic identity politics reinstate old forms of social segregation, such as class, race, and gender, through defaults and paradigmatic assumptions about the homophilic nature of connection. Instead of providing a more “objective” basis of decision making, machine-learning algorithms deepen bias and further inscribe inequality into media. Yet pattern discrimination is an essential part of human-and nonhuman-cognition. Bringing together media thinkers and artists from the United States and Germany, this volume asks the urgent questions: How can we discriminate without being discriminatory? How can we filter information out of data without reinserting racist, sexist, and classist beliefs? How can we queer homophilic tendencies within digital cultures?

What it means when media moves from the new to the habitual-when our bodies become archives of supposedly obsolescent media, streaming, updating, sharing, saving. New media-we are told-exist at the bleeding edge of obsolescence. We thus forever try to catch up, updating to remain the same. Meanwhile, analytic, creative, and commercial efforts focus exclusively on the next big thing: figuring out what will spread and who will spread it the fastest. But what do we miss in this constant push to the future? In Updating to Remain the Same, Wendy Hui Kyong Chun suggests another approach, arguing that our media matter most when they seem not to matter at all-when they have moved from "new" to habitual. Smart phones, for example, no longer amaze, but they increasingly structure and monitor our lives. Through habits, Chun says, new media become embedded in our lives-indeed, we become our machines: we stream, update, capture, upload, link, save, trash, and troll. Chun links habits to the rise of networks as the defining concept of our era. Networks have been central to the emergence of neoliberalism, replacing "society" with groupings of individuals and connectable "YOUS." (For isn't "new media" actually "NYOU media"?) Habit is central to the inversion of privacy and publicity that drives neoliberalism and networks. Why do we view our networked devices as "personal" when they are so chatty and promiscuous? What would happen, Chun asks, if, rather than pushing for privacy that is no privacy, we demanded public rights-the right to be exposed, to take risks and to be in public and not be attacked?

A theoretical examination of the surprising emergence of software as a guiding metaphor for our neoliberal world. New media thrives on cycles of obsolescence and renewal: from celebrations of cyber-everything to Y2K, from the dot-com bust to the next big things-mobile mobs, Web 3.0, cloud computing. In Programmed Visions, Wendy Hui Kyong Chun argues that these cycles result in part from the ways in which new media encapsulates a logic of programmability. New media proliferates "programmed visions," which seek to shape and predict-even embody-a future based on past data. These programmed visions have also made computers, based on metaphor, metaphors for metaphor itself, for a general logic of substitutability. Chun argues that the clarity offered by software as metaphor should make us pause, because software also engenders a profound sense of ignorance: who knows what lurks behind our smiling interfaces, behind the objects we click and manipulate? The combination of what can be seen and not seen, known (knowable) and not known-its separation of interface from algorithm and software from hardware-makes it a powerful metaphor for everything we believe is invisible yet generates visible, logical effects, from genetics to the invisible hand of the market, from ideology to culture.

A work that bridges media archaeology and visual culture studies argues that the Internet has emerged as a mass medium by linking control with freedom and democracy. How has the Internet, a medium that thrives on control, been accepted as a medium of freedom? Why is freedom increasingly indistinguishable from paranoid control? In Control and Freedom, Wendy Hui Kyong Chun explores the current political and technological coupling of freedom with control by tracing the emergence of the Internet as a mass medium. The parallel (and paranoid) myths of the Internet as total freedom/total control, she says, stem from our reduction of political problems into technological ones. Drawing on the theories of Gilles Deleuze and Michel Foucault and analyzing such phenomena as Webcams and face-recognition technology, Chun argues that the relationship between control and freedom in networked contact is experienced and negotiated through sexuality and race. She traces the desire for cyberspace to cyberpunk fiction and maps the transformation of public/private into open/closed. Analyzing "pornocracy," she contends that it was through cyberporn and the government's attempts to regulate it that the Internet became a marketplace of ideas and commodities. Chun describes the way Internet promoters conflated technological empowerment with racial empowerment and, through close examinations of William Gibson's Neuromancer and Mamoru Oshii's Ghost in the Shell, she analyzes the management of interactivity in narratives of cyberspace. The Internet's potential for democracy stems not from illusory promises of individual empowerment, Chun argues, but rather from the ways in which it exposes us to others (and to other machines) in ways we cannot control. Using fiber optic networks-light coursing through glass tubes-as metaphor and reality, Control and Freedom engages the rich philosophical tradition of light as a figure for knowledge, clarification, surveillance, and discipline, in order to argue that fiber-optic networks physically instantiate, and thus shatter, enlightenment.