Last Words | Large Language Models and the AI Apocalypse
What kind of meaning can machines make — and why does it matter that it’s not the same as ours?
Anthropologist Paul Kockelman's Last Words (2024) offers a rigorous but accessible account of how large language models actually work — and why the meaning they produce is fundamentally different from human meaning-making. Drawing on the semiotics of C.S. Peirce, Kockelman’s witty and insightful pamphlet shows how LLMs are trained to predict word-word relations, not word-world relations, which explains both their uncanny fluency and their systematic blind spots. The result is a compact, essential guide to cutting through the hype: not a dismissal of AI, but a precise account of what it can and cannot do — and who profits from the confusion.
Data, Now Bigger and Better!
Data is too big to be left to the data analysts. Data: Now Bigger and Better! brings together researchers whose work is deeply informed by the conceptual frameworks of anthropology—frameworks that are comparative as well as field-based. From kinship to gifts, everything old becomes rich with new insight when the anthropological archive washes over “big data.” Bringing together anthropology’s classic debates and contemporary interventions, the book counters the future-oriented speculation so characteristic of discussions regarding big data. Drawing on the long-standing experience in industry contexts, the contributors also provide analytical provocations that can help reframe some of the most important shifts in technology and society in the first half of the twenty-first century.