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Hate is being reinvented. Over the last two decades, online platforms have been used to repackage racist, sexist and xenophobic ideologies into new sociotechnical forms. Digital hate is ancient but novel, deploying the Internet to boost its allure and broaden its appeal. To understand the logic of hate, Luke Munn investigates four objects: 8chan, the cesspool of the Internet, QAnon, the popular meta-conspiracy, Parler, a social media site, and Gab, the "platform for the people." Drawing together powerful human stories with insights from media studies, psychology, political science, and race and cultural studies, he portrays how digital hate infiltrates hearts and minds

Hate is being reinvented. Over the last two decades, online platforms have been used to repackage racist, sexist and xenophobic ideologies into new sociotechnical forms. Digital hate is ancient but novel, deploying the Internet to boost its allure and broaden its appeal. To understand the logic of hate, the author investigates four objects: 8chan, the cesspool of the Internet, QAnon, the popular meta-conspiracy, Parler, a social media site, and Gab, the "platform for the people." Drawing together powerful human stories with insights from media studies, psychology, political science, and race and cultural studies, he portrays how digital hate infiltrates hearts and minds.

Hate is being reinvented. Over the last two decades, online platforms have been used to repackage racist, sexist and xenophobic ideologies into new sociotechnical forms. Digital hate is ancient but novel, deploying the Internet to boost its allure and broaden its appeal. To understand the logic of hate, Luke Munn investigates four objects: 8chan, the cesspool of the Internet, QAnon, the popular meta-conspiracy, Parler, a social media site, and Gab, the »platform for the people.« Drawing together powerful human stories with insights from media studies, psychology, political science, and race and cultural studies, he portrays how digital hate infiltrates hearts and minds.

Territory is shifting. No longer defined by the dotted line of the border or the national footprint of soil, today's territories are enacted through data infrastructures. From subsea cables to server halls, these infrastructures underpin new forms of governance, shaping subjects and their everyday lives. Technical Territories moves from masked protestors in Hong Kong to asylum-seekers in Christmas Island and sand miners in Singapore, exploring how these territories are both political and visceral, altering the experience of their inhabitants.

Infrastructures have now become geopolitical, strategic investments that advance national visions, extend influence, and trigger trade wars. Yet at the same time, these technologies also challenge sovereignty as a bounded container, enacting a more distributed and decoupled form of governance. Such "technical territories" construct new zones where subjects are assembled, rights are undermined, labor is coordinated, and capital is extracted. The stable line of the border is replaced by more fluid configurations of power. Luke Munn stages an interdisciplinary intervention over six chapters, drawing upon a wide range of literature from technical documents and activist accounts, and bringing insights from media studies, migration studies, political theory, and cultural and social studies to bear on these new sociotechnical conditions.

I. The myth of automated autonomy. The fantasy of full automation -- Spotty automation and less-than-human workers -- II. The myth of automation everywhere. Technology in context, technology as culture -- Automation on the ground -- III. The myth of automating everyone. Automation's racialized fallout -- Automation's gendered inequality -- Conclusion : automation is not our future.

For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind "autonomous" processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of "the human" at the heart of automation claims. But labor is socially stratified and so automation's fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don't) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the "future of work."

Contemporary power manifests in the algorithmic. And yet this power seems incomprehensible: understood as code, it becomes apolitical; understood as a totality, it becomes overwhelming. This book takes an alternate approach, using it to unravel the operations of Uber and Palantir, Airbnb and Amazon Alexa. Moving off the whiteboard and into the world, the algorithmic must negotiate with frictions - the 'merely' technical routines of distributing data and running tasks coming together into broader social forces that shape subjectivities, steer bodies, and calibrate relationships. Driven by the imperatives of capital, the algorithmic exhausts subjects and spaces, a double move seeking to both exhaustively apprehend them and exhaust away their productivities. But these on-the-ground encounters also reveal that force is never guaranteed. The irreducibility of the world renders logic inadequate and control gives way to contingency.

From pandemics to political campaigns, online misinformation has become acute. In response, a plethora of interventions have been offered, from debunking and prebunking to fact-checking and labeling. While the technical efficacy of these "solutions" are debatable, I suggest a more fundamental failure: they rely on a humanlike caricature, a rational and ethical figure who only needs better facts to disavow misguided misinfo practices. Instead I argue that misinformation studies must incorporate a more holistic human. Drawing from the broader humanities, this article conceptualizes the actually-existing human who can be emotional, factional, and bigoted – all qualities instrumentalized and amplified by online media. Reinserting this missing figure reintroduces agency and antipathy into misinformation studies. Misinformation is not something done to innocent subjects who merely need to be educated, but is an active practice shaped by identity and sociality that reflects the contradictions and frictions intrinsic to human nature.

AbstractAs the awareness of AI's power and danger has risen, the dominant response has been a turn to ethical principles. A flood of AI guidelines and codes of ethics have been released in both the public and private sector in the last several years. However, these aremeaningless principleswhich are contested or incoherent, making them difficult to apply; they areisolated principlessituated in an industry and education system which largely ignores ethics; and they aretoothless principleswhich lack consequences and adhere to corporate agendas. For these reasons, I argue that AI ethical principles are useless, failing to mitigate the racial, social, and environmental damages of AI technologies in any meaningful sense. The result is a gap between high-minded principles and technological practice. Even when this gap is acknowledged and principles seek to be "operationalized," the translation from complex social concepts to technical rulesets is non-trivial. In a zero-sum world, the dominant turn to AI principles is not just fruitless but a dangerous distraction, diverting immense financial and human resources away from potentially more effective activity. I conclude by highlighting alternative approaches to AI justice that go beyond ethical principles: thinking more broadly about systems of oppression and more narrowly about accuracy and auditing.

Sophisticated modelling and machine learning technologies, underpinned by cloud computing, are increasingly being deployed within the oil and gas industry. As the easy energy pockets of the past dry up, such technologies promise to locate deposits, increase extraction and optimize production. These high-performance computing technologies require vast infrastructures, a requirement that, in the midst of a climate crisis, has seen a new alliance between Big Tech and Big Oil. Drawing on grey literature from press releases to whitepapers and tech demonstrations, this article investigates these alliances between oil companies and tech companies, along with the rise of cloud-driven processes in energy discovery and production – in short, the new intersection between the computational and the petrotechnical. How might the extractive violence of the 'petro' be intensified and diversified by the 'technical' of cloud computing? It argues that cloud computing does indeed contribute to more efficient processes of energy extraction, but that this effectively means an optimization of ecological destruction, assisting the industry in more rapidly and comprehensively damaging diverse forms of life. Understanding the logics of these technologies and the political economy that underpins them is crucial for intervening effectively against these environmentally devastating operations.

Data centers and undersea cables allow information to be transmitted, stored, and processed. Yet, more than passively housing knowledge, information infrastructures actively shape knowledge. Infrastructures facilitate a certain use case, privileging some forms of knowledge while ignoring others. And infrastructures are material investments by states or corporations at a particular site, solidifying their knowledge-production, while marginalizing alternatives. These conditions are exemplified by two sites in Tseung Kwan O, Hong Kong. The TKO Express is a private undersea cable that offers its clients high-speed connectivity between financial centers, supporting the "fast knowledge" of finance and trading, while ignoring slower or more social forms of intelligence. The TKOIE industrial estate allocated land to a data center rather than a community center, prioritizing the production of corporate, proprietary knowledge over local and communal knowledge. The article reworks the concept of epistemic infrastructures to stress how such facilities influence what can be known and what remains unknown.

Rather than being unprecedented, contemporary technologies are the most sophisticated instances of a long-standing dream: if space could be more comprehensively captured and coded, it could be more intensively capitalized. Two moments within this lineage are explored: maritime insurance of slave ships in the eighteenth century, and the Black-Scholes model of option pricing from the twentieth century. Maritime insurance rendered the unknown space of the ocean knowable and therefore profitable. By collecting information at Lloyds, merchants developed a map of threat within the Atlantic, and by writing a 10 percent buffer into slave-ship contracts they internalized contingency. This codification of risk pressured captains and established a logic for the violence enacted on the ship's human "cargo." The Black-Scholes formula of option pricing sought to codify the ocean of risk represented by the financial market. The formula mapped stock movements into a knowable stochastic equation. Traders could quantify and hedge against the unpredictable, rendering the stock market a space of riskless profit. However, the 2008 financial crash demonstrated the limits of spatial calculation. Taken together, these two moments demonstrate the historical continuity of a core imperative to exhaustively capitalize space. This historicization also foregrounds the racialized inequalities coded within these informatic logics. Against the bright innovation narratives of technology, this article stresses a longer and darker lineage based on inequality and dispossession.