How AI is rewiring our social fabric—and how we can better shape our future.

The age of AI is not what you think. Rather than ushering in a fourth Industrial Revolution, AI has become a crucial social infrastructure of everyday life. It's embedded in the tools, platforms, and systems that organize our most intimate lives and our interactions with the most fundamental institutions of society, from government agencies to banks and schools. In these linkages are embedded assumptions about who we are, what we can do, and where we belong.

In Predicted: How AI Is Restructuring Social Life (U California Press, 2026), Mona Sloane offers a pragmatic framework for understanding these transformations around prediction, classification, and linearity, proposing that we think about AI as a social arrangement that we coproduce. Drawing on over a decade of empirical research and real-world examples, this book invites us to see AI for what it is: deeply social, deeply political, and open to change. Clear-eyed and provocative, Predicted is a call to reclaim deliberations about progress and innovation as a public good and to ensure that the futures we chart are the ones we choose—together.

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What does it mean to learn when algorithms increasingly shape how knowledge is produced, organized, and interpreted? Editors Elizabeth de Freitas, Matthew X. Curinga, and Ezekiel J. Dixon-Román join Shreya Urvashi to talk about their book Learning Under Algorithmic Conditions (U Minnesota Press, 2026), a collection that examines how artificial intelligence and computational systems are changing education, cognition, and ideas of human intelligence. The editors discuss the complexities of algorithm, training data as curriculum, AI bias, and the concept of more-than-human learning. They also explore the relationship between contemporary technologies and colonial forms of reason, the limits of treating bias as a purely technical problem, and what happens to human agency as learning becomes increasingly entangled with algorithmic systems.

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Today I’m speaking with Garrison Lovely, technology journalist and author of the new book, Obsolete: The AI Industry's Trillion Dollar Race to Replace Us — and How to Stop It (OR Books, 2026). Artificial intelligence is perhaps the most discussed and most misunderstood topic today. Even to the experts and captains of industry, the frontier large language models are essentially black boxes. AI poses many reasons to be both skeptical and optimistic, yet it also poses a fundamental threat to our current economic order and social contract. If AI succeeds, what will it mean for workers, consumers, and the huddled masses who do not own the multi-trillion dollar companies directing the global economy? Garrison Lovely has coined the term, Obsoleting Project to describe the goal of AI companies to build machines that outperform humans on nearly every task. It reimagines technology, not as a tool of efficiency, but rather as a tool that replaces labor full-stop. What happens to our society if they succeed? Garrison’s Obsolete is a fantastic round-up of the most important social and economic challenges posed by AI. I’m thrilled today to have Garrison on The Truth About Bullshit to understand a bit more about the Obsoleting Project.

Caleb Zakarin is CEO and Publisher of the New Books Network.

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