In my conversation with Professor Pablo F. Gómez about his new book, Bloody Numbers: The Early Atlantic Slave Trade and the Invention of Modern Corporeality, published by the University of Chicago Press in 2026.

Our conversation explored the unsettling relationship between slavery, the body, measurement, and knowledge. What does it mean to measure a human body within a system that has already reduced that person to a commodity? And what happens when numbers that appear neutral become entangled with violence, commerce and exploitation?

What stayed with me is the book’s invitation to think differently about numbers. Behind measurements of height, weight, health, disease and mortality were human beings whose lives could not be contained by the data recorded about them.

These questions are not only historical. We live in an increasingly quantified world, where bodies, health, productivity and risk are constantly measured and transformed into data.

So perhaps one question we should keep asking is: Who is doing the counting, why are they counting, and what happens to the people being counted?

I invite you to listen to our conversation and reflect with us on the histories behind the numbers we encounter today.

Amisah Bakuri (PhD) is an Assistant Professor in the Faculty of Social Sciences and Humanities at Vrije Universiteit Amsterdam. Her work explores the intersections of religion, sexuality, gender, and migration, especially within African diasporic communities in the Netherlands.

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Since the advent of computers, society has fantasized about conversing with machines. In Divination Engines: Natural Language Processing, Artificial Intelligence, and the Making of Algorithmic Culture (University of Chicago Press, 2026), Dr. Xiaochang Li shows readers how that dream both fueled the demand for data and set the stage for today’s generative AI. 

With original research and clear explanations, Dr. Li elucidates the origins of what’s known as natural language processing (NLP) and the heated twentieth-century debates between computer scientists, linguists, and communication engineers that shaped today’s technology. Starting with early devices that recorded, analyzed, and attempted to interpret human speech, she demonstrates how computer speech recognition, particularly efforts led by Bell Labs and IBM, advanced technology by deemphasizing linguistic meaning in favor of statistical prediction. In other words, researchers gradually abandoned systems that sought to understand human language, opting instead for work-arounds that simply predicted patterns in speech and text data. That solution became incredibly and surprisingly adaptable. As Dr. Li reveals, transforming linguistic questions into engineering ones ushered in the routine operation of search engines, spam filters, and the varied content sorting and recommendation mechanisms that regulate the access, circulation, and legitimacy of information across every platform. But this has all come at the cost of forever requiring copious and ever-growing amounts of new data.

At its core, Divination Engines illuminates how the artifacts of human communication—speech, text, and images—have become both the fodder for and products of computers. This connection between communication and computation, Li shows, has given rise to data-driven analytics, machine learning, and today’s algorithmic culture.

This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda’s interviews on New Books with Miranda Melcher, wherever you get your podcasts. 

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What if, every time you wanted to write down 1,000,000, you had to draw a picture of a god? And what if that number were the biggest you had a symbol for? If you were doing math in ancient Egypt, those were the rules: anything bigger broke math.
As mathematician Richard Elwes shows in Huge Numbers: A Story of Counting Ambitiously, from 4 1/2 to Fish 7 (Basic Books, 2026)this is the strange story of math. Even today, writing down some numbers is beyond us: try it with all the zeroes in a googolplex, or an outrageous alien number like TREE(3). Safer not to try: even harnessing every particle in the universe, you wouldn’t come close. But this book is no mere bestiary of numerical monsters. It shows how, by hunting down and studying ever-bigger numbers, arithmetic has reshaped human thought and made our modern era of science and computation possible.
Where many math books celebrate abstract algebra or ineffable infinities, Huge Numbers is both more practical and far weirder. It reveals a world where most numbers remain out of reach until we discover how to chase them down and tame them, and so remake our world again.

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