Orlando and Oliver studied philosophy together 30 years ago. Their shared love for philosophy, design, and technology reunited them to discuss AI and the future.

AI and Ethics -

When I first used Dall-E in January 2021, I input some text, I think it was a resin chair inspired by a cactus (I had Gaetano Pesce on my mind).

Eryk Salvaggio says we must dispense with myths if we are to think more clearly about what AI actually is and does.

A text about reading AI images as infographics.

A study published in the Journal of Hospitality of Marketing & Management finds that consumers are very much turned off by products that say they are “AI-powered”

“The path generative AI is on is wrong for us”

Portfolio and Archive

More than ever, we’re challenged to define what’s valuable about being human.

The originator of the Gaia theory offers the vision of a future epoch in which humans and artificial intelligence together will help the Earth survive.James ...

What is AI? A dominant view describes it as the quest "to solve intelligence" - a solution supposedly to be found in the secret logic of the mind or in the deep physiology of the brain, such as in its complex neural networks. The Eye of the Master argues, to the contrary, that the inner code of AI is shaped not by the

Creative Pattern Recognition is a hybrid publication that explores the intersection of artificial intelligence and creative practice. It covers a wide range of topics such as the role of AI in art and design, addressing the impact and potential of AI on creative practice. It also highlights the opportunities and challenges presented by AI tools, the evolution of the field, and the potential for AI to enhance human creativity and explore uncharted artistic territories. Furthermore, it explores the ethical considerations surrounding AI, including the impact on creative jobs and the importance of demystifying AI to address societal concerns. Through interviews, reflections and analytical pieces, Creative Pattern Recognition provides a comprehensive, situated overview of the current landscape of AI in creative practice and formulates an answer to the question of why creatives should engage with AI and how to approach it.

Grief-laden vitriol directed at AI fails to help us understand paths to better futures that are neither utopian nor dystopian, but open to radically weird possibilities.

An urgent intervention rooted in the militant liberation struggles of the most oppressed within the arena of global computational racial capitalism.

Within the last decade a large corpus of work in HCI as well as the commercial design practice has focused on systematically addressing questions of ethics, values and moral considerations embedded in the design of digital technology. Recent critiques have highlighted that these efforts fall short of actual transformative impact. We use the sociological concept of imaginaries to argue that value and ethics work needs to be considered within the larger context of socially shared visions of a desirable future and outline how existing sociotechnical imaginaries pre-frame contexts in which value work is deployed. We demonstrate that imaginaries provide the language and conceptual framework necessary to address underlying ethical worldviews before ethics driven design methods and toolkits can be successfully employed. Finally we suggest how to engage imaginaries to facilitate a broader shift towards a more politically sensitive approach to designerly value work.

As AI shapes more and more of our experience online, we think it’s not enough to comment from the sidelines—we need to also get actively engaged in actually solving the problems vexing consumers

Techno-utopianism is dead: Now is the time to pay attention to the inequality, marginalization, and biases woven into our technological systems.This book sou...

Thinking about the state of technology today necessarily means thinking about a number of interrelated but distinct entities. Considering the nuts and bolts of a news story in which, say, some corporate machine vision technology was found to be racially discriminatory can often mean having to study business practices, data sciences, specific suites of tools that can lay a claim to the moniker of AI, assemblages of hardware and software, platform infrastructures with machines slotted away in hot data-center basements in tax havens, human-computer interactions and perceptions, and academic/industry discourses within any of the aforementioned, not to mention the geopolitical and historical situation of it all, which may further call into question where, say, “American” literature can uniquely intersect with technologies splayed awkwardly across, and not always along, the traditional geopolitical and cultural fault lines. In such a scenario, the flag of “Critical AI and (American) Literature,” by its very constitution, carries several sigils, including those of big data and literature and of computational culture and literature, as well as American studies and global technological sovereignties. Focused on the more critical end of these studies, this review brings together three new multiauthored books to ask what we critique when we critique technology today.Scholars interested in literature and technology—usually found in disciplines and departments such as languages and literatures, cultural studies, science studies, and media studies—have long been producing pathbreaking critical thought about various sociotechnical phenomena. From reading technologies themselves using literary critical methods—N. Katherine Hayles, Donna Haraway, Friedrich Kittler, Wendy Chun, Matthew Kirschenbaum, Rita Raley, Lisa Gitelman, and Alexander Galloway all come to mind here—to studying literary expressions of technological worlds (see, e.g., work by Fredric Jameson, Bruce Clark, Laura Otis, Steven Shaviro, Sherryl Vint, and Colin Milburn), literary criticism has been a bellwether of technology critique for several decades now. A brief look at such critique through the ages shows us the varied moods that orient studies of these technologies, with AI just being the latest in this series that once featured the internet, the personal computer, hypertext, cellphone, and metadata. Where there was once a utopian dream with the expansion of networks in the 1990s, or a reluctant acceptance that became a residual flicker of counterprogrammatic hope that technologies can be reappropriated by radical social forces in late 2010s, there is now, in critical work collected here, largely anger and disappointment. Every day, as news cycles tell tales of unchecked tech monopolies roughly intruding into our social, political, and psychic lives, and rarely for the good, these authors find themselves angry—really angry—about the state of our technologies and what they have wrought. On the one hand, such anger indexes our historical condition and informs our engagement with technology today. On the other hand, it forces us to ask what we are actually angry about, and what can be done instead.The primary example of this mood may be found in Your Computer Is on Fire, edited by Thomas S. Mullaney, Benjamin Peters, Mar Hicks, and Kavita Philip. This volume is a startlingly direct collection of essays that, for the most part, all do what they say; the overarching purpose of the volume is, in fact, a call to action that signals a diffused state of emergency in various corners of computational cultures (6). The three parts of the book—“Nothing Is Virtual,” “This Is an Emergency,” and “Where Will the Fire Spread?”—contain chapters that are thematically and methodologically varied but all united by their clear and accessible critiques that point out how inequalities and discriminations are enabled and exacerbated by technological systems today. To note a few, Nathan Ensmenger’s “The Cloud Is a Factory,” which uses Amazon as a case study for the infrastructural reinscription of older techniques of capital used by Sears and Standard Oil, is an excellent breakdown of the material behind the supposedly virtual cloud (29); Ben Peters’s “A Network Is Not a Network” accounts for the role of institutional behavior in the constitution of large-scale networks (71); Mar Hicks, through an analysis of gender discrimination in mid-twentieth-century technology labor sector, claims that “Sexism Is a Feature, Not a Bug” in tech economies and communities (135); Safiya Umoja Noble tells us that our robots aren’t neutral (199); Janet Abbate takes on tech sector’s consideration of coders using the pipeline model—the discourse that encourages getting more women and minorities to learn coding earlier and faster so as to facilitate a smoother and more expansive flow of more diverse labor into the infamously white and masculine technology sector—to show how “Coding Is Not Empowerment” (253); Ben Allen magisterially demonstrates how the same genre of technical hacks can be read as playful or criminal depending on power dynamics (273); and Paul Edwards studies platforms, which he calls fast infrastructures, as he takes up exemplars from South Africa and Kenya to suggest that these fleeting operational levers represent the next model of corporate infrastructural dominance (313). The volume, then, contains a series of related, but not necessarily coagulated, critiques of technology and its sociocultural conditions.Technoprecarious, collectively authored by the Precarity Lab (the contributing team comprises Cassius Adair, Iván Chaar López, Anna Watkins Fisher, Meryem Kamil, Cindy Lin, Silvia Lindtner, Lisa Nakamura, Cengiz Salman, Kalindi Vora, Jackie Wang, and McKenzie Wark) reads not like an edited collection but more like a short manifesto written by scholars with complementary orientations. The different sections of the book—among them “The Undergig,” “The Widening Gyre of Precarity,” “Automating Abandonment,” “Fantasies of Ability,” and“Dispossession by Surveillance”—come together to form a patchwork of commentaries, most well rooted in original cultural, sociotechnical, anthropological, and historical research, that all very playfully point out the exacerbation of precarity wrought by, with, and through digital technologies today. The titular technoprecarity, for the collective, is “the premature exposure to death and debility that working with or being subjected to digital technologies accelerates” (1). Technoprecarity here shows up in snippets that plug into work on surveillance, carceral systems, toxicity, and administrative failures, among other nodes of inquiry. The final two chapters feature a Haraway-esque hope for radical reappropriation listing the Detroit Digital Stewards Program, which features groups that help underprivileged communities gain access to technologies as tools of communication, and the use of open-source maps in Palestine as examples to be followed for practices of techno-oriented care (74–86). There is a sincere attempt here, not unlike the penultimate contribution in Your Computer Is on Fire, “How to Stop Worrying about Clean Signals and Start Loving the Noise” by Kavita Philip (363), to find a nugget or two of hope in the middle of the general condition of technoprecarity being described.Uncertain Archives: Critical Keywords for Big Data, edited by Nanna Bonde Thylstrup, Daniela Agostinho, Annie Ring, Catherine D’Ignazio, and Kristin Veel, is a six-hundred-page collection that features sixty-one keyword entries, altogether providing a Raymond Williams–style vocabulary for critical studies of data and AI. Considering big data as an uncertain archive—drawing from archival theory and critical data studies while thinking about the latent possibilities of aggregation as presented by big data today—the collection features short, punchy nuggets of wisdom that offer a polysemic understanding of the kinds of critical thought different disciplines can offer to studies of big data and AI at large. The entries vary widely in style, tone, content, and orientation. Overlapping questions of epistemologies (“Quantification” by Jacqueline Wernimont, “Ethics” by Louise Amoore, “Unpredictability” by Elena Esposito, “Remains” by Tonia Sutherland), alterity and discrimination (“Abuse” by Sarah Roberts, “(Mis)Gendering” by Os Keyes), power (“DNA” by Mél Hogan, “Instrumentality” by Luciana Parisi, “Organization” by Timon Beyes), aesthetics (“Demo” by Orit Halpern; a brilliant, poetic one on “Throbber” by Kristoffer Ørum; “Visualization” by Johanna Drucker), infrastructures (“Cooling” by Nicole Starosielski, “Supply Chain” by Miriam Posner, “Field” by Shannon Mattern), and socialities (“Values” by John S. Seberger and Geoffrey C. Bowker, “Proxies” by Wendy Hui Kyong Chun, Boaz Levin, and Vera Tollmann; “Self-Tracking” by Natasha Dow Schüll) all sit alongside questions near and dear to literary critical approaches (“Digital Humanities” by Roopika Risam, “File” by Craig Robertson, “Misreading” by Lisa Gitelman). In performing the immensely unenviable task of shepherding sixty-eight other scholars from across the world into one contained collection, the editors here provide a deliberately fragmented mise-en-scène of critical data studies as it unfolds across several corners of academia today. Juggling several different approaches, Uncertain Archives does not easily offer a shared through line. Nevertheless, it can be read as a collection trying to enumerate the various evaluative frameworks that can be applied to/in critical (big) data studies; most terms offered here—some of which are compressed versions based on the concepts outlined in the contributors’ monographs and articles—can be taken as pedagogical scaffolds or starting points for a broader set of research inquiries. And big data here shows up as nebulous and tentacular, both in its contemporary material reach and in its ...

Problems of bias and fairness are central to data justice, as they speak directly to the threat that ‘big data’ and algorithmic decision-making may worsen already existing injustices. In the United...

Can technology resolve social problems by reducing them to engineering challenges? In the 1960s, Alvin Weinberg answered yes, popularizing the term “techno-fix”

Overheated rhetoric about a U.S.-China AI arms race need not distract us from common ground on how advanced technology can be regulated across cultural and national boundaries.

I’ve been struggling to articulate this idea, and maybe the problem is that it’s actually kind of simple once you put it out there, and there’s really no good reason to unpack a whole case for it once you put the thought on paper.

We can still have the internet we want — but we have to try new business models