5 Upcoming Academic Books on AI, Archiving, and Data Mining

Our most hotly anticipated books for fall!

Posted on October 8, 2025 in Blog Posts

With the start of October, we’re gearing up for long, cool nights perfect for reading a good book. But let’s put aside those pumpkin-spice romances and cozy mysteries, and swan into spooky season by thinking about our technological future. In this installment of our seasonal preview of academic titles we’re looking forward to, we’ve selected five books that represent a range of topics in media, information, and internet studies that we think will make for good company on these fall nights.

Let’s get started!

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🗑️ Enshittification: Why Everything Suddenly Got Worse and What To Do About It, by Cory Doctorow (Verso)

Cory Doctorow has made a name for himself by giving internet users a word for describing, as the subtitle of his book puts it, “why everything suddenly got worse and what to do about it.” For Doctorow, “enshittification” refers to the process by which the companies behind online platforms offer a user experience that is eroded, monetized, and destroyed over time. Doctorow has written extensively on this topic on X/Twitter and across various venues, and this volume consolidates his theory of enshittification and, enticingly, outlines his solutions.

If you haven’t read Doctorow’s work before or if the term “enshittification” is new to you, I highly recommend checking out this volume. Doctorow has done the important work of providing a vocabulary for interacting with our new digital environments, and this book shouldn’t be missed.

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⚙️ The AI Matrix: Profits, Power, Politics, by Daniel Mügge, Regine Paul, and Vali Stan (Columbia)

When talking about the ethical costs of AI, many people understandably focus on the environmental tolls of AI’s vast energy consumption. Less often discussed is the political economy, spanning the US’s geopolitical ambitions for AI and the tolls of AI on global economies. These stories dot the headlines, but The AI Matrix brings them into a cohesive narrative about global politics. Judging from the prepublication materials, their narrative centers on AI’s “unevenness”—between regions, economic sectors, and actors—which provides an important counterargument to technologists’ favored narrative of “progress.” This book will be an important guidepost in conversations surrounding AI ethics.

🔲 Negative Media: Erasure and the Limits of Retention, by Ella Klik (Stanford)

This pick is for all the archivists in the audience. In Negative Media, Klik tells a historical narrative about loss, erasure, and deletion within storage technologies from the 19th century to the present. In spite of the efforts to preserve texts, data, and images, media is often lost, sometimes within the process of preservation. According to the book description, Klik argues that “negation is not a design flaw but a process intentionally woven into the very fabric of these systems.”

This book promises to help readers rethink the acts of preservation, whether digital or analog, and offer a new way of thinking about our present age of mass data retention.

🛑 How Progress Ends: Technology, Innovation, and the Fate of Nations, by Carl Benedikt Frey (Princeton)

“Progress” has long been the watchword of Western civilization, uniting its political, economic, and technological ambitions and making them seem inevitable. Frey offers a revisionist perspective of this concept by looking at the past 1,000 years of technological development. He suggests that stagnation, rather than progress, has governed much of this period. His work examines societies that have both prospered and perished due to rapid technological changes, and considers the conditions that are necessary for new technologies to benefit civilization.

Though his book spans 1,000 years, Frey’s eye is clearly on AI, and the story he weaves offers some much-needed perspective on technological development beyond “the next big thing.”

⛏️ Text and Data Mining Literacy for Librarians, ed. by Whitney Kramer, Iliana Burgos, and Evan Muzzall (ACRL)

It isn’t a conflict of interest for us to highlight this new book out of ACRL because we’re genuinely excited for it. Text and data mining refers to the process of using digital software and programs to get useful information out of large sets of data and content. This collection surveys work that libraries have undertaken to promote literacy in this area. It outlines what this literacy entails, gives case studies of libraries that have employed it, and explores the benefits of text and data mining in research.

Libraries have become massive repositories for data, and the many contributors to this book help answer the crucial question, What can we do with it? The answer: quite a lot.

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