Data & Society

In Silicon Valley, economic, political, and state power have fused, and tech oligarchs like Elon Musk, Jeff Bezos, Mark Zuckerberg are reshaping the world in their image. Two new books examine this decades-long trajectory from very different angles: In Muskism: A Guide for the Perplexed, Quinn Slobodian and Ben Tarnoff explore how figures like Musk embody a social system where technological infrastructure — from satellites to social media platforms — pave the road to a “freedom” rooted in reactionary geopolitics and racial hierarchies enforced by militarized violence. In Against Tech Oligarchy: Worker Resistance in the World’s Most Powerful Industry, JS Tan and Clarissa Redwine write about how many tech workers were attracted to the industry by a different kind of freedom, one that promised a more connected and democratic world. While in recent years this façade has crumbled, the authors show how the “dry kindling” that both set off and consumed tech workers’ collective action against oligarchic powers had been present in Silicon Valley all along. Learn more about the event: https://datasociety.net/research-library/power-and-resistance-in-the-age-of-tech-oligarchy/.Purchase your copy of Against Tech Oligarchy: Worker Resistance in the World’s Most Powerful Industry and Muskism: A Guide for the Perplexed.

To hear many in the tech industry tell it, data centers will bring wealth and prosperity not only to those who build them, but to the communities that ultimately live with and around them. But drawing a longer historical arc is essential: AI is proposed as a new industrial moonshot in communities that have already seen the rise and fall of steel factories, coal plants, fracking infrastructure, and more. Today’s companies are trying to sell communities on yet another industrial vision.This time, those communities are raising concerns about some of data centers’ more visible impacts, including their intensive use of resources, while contending with a host of unknowns related to environmental costs, quality of life, and the future. In the face of yet another generation of rapid corporate development and promises of trickle-down benefits, community members and activists across political lines are not sitting on the sidelines. They are organizing and engaging fellow residents, media, and government to demand their say in how data centers operate and impact the places they live.The event was anchored by the launch of Data & Society’s report, The AI Factory: Data Centers, Power and Resistance in Late Industrial Pennsylvania, a landmark study emerging out of eighteen months of field research in the Keystone State, as well as Pulitzer Center-supported reporting on data center development by The Texas Tribune.

The United States census, conducted every ten years, is one of the world’s oldest and biggest data-making endeavors, and one of the country’s most consequential. In her urgent new book 'Data Are Made, Not Found: A Story of Politics, Power, and the Civil Servants Who Saved the US Census,' professor, researcher, and Data & Society founder danah boyd explores what it took for the Census Bureau to make the 2020 census, amid a global pandemic and natural disasters, and while navigating political forces that constrained the budget, micro-managed the schedule, and attacked statisticians’ methods. Despite these challenges, civil servants saved the 2020 census, but future censuses — and other data-making efforts related to elections, health, and the economy — are precarious. By documenting the perspectives of government workers in Data Are Made, Not Found, boyd provides a rare glimpse into what it takes to make democracy’s data and shows clearly why protecting democracy means protecting the people and institutions that produce that data. 

AI agents have begun to move from speculative promise into everyday deployment. They translate high-level goals into plans and carry them out across connected digital environments. Agent builders often promise that users will remain in control through approval prompts and pause buttons. Yet these safeguards work only when users can recognize a mistake and intervene before its consequences cascade. Drawing on fieldwork in a computational biology laboratory, Data & Society’s primer The Oversight Fallacy examines what effective oversight of AI Agents requires in practice.

As AI is integrated into scientific practice, the practice of science itself is changing. AI models that summarize, categorize, simulate, and predict not only stand to accelerate scientific research; they now sit inside these practices, alternately enhancing and eroding craft while shifting how questions are posed, what counts as evidence, how tacit judgment is taught and exercised, and reshaping trust in results.   Dr. Kristin M. Branson (@kristinmbranson.bsky.social) is a senior group leader at the Howard Hughes Medical Institute’s (HHMI) Janelia Research Campus in Ashborn, Virginia. Dr. Lisa Messeri (@lmesseri.bsky.social) is an associate professor of sociocultural anthropology at Yale University.  Dr. Nicole C. Nelson (@nicolecnelson.bsky.social) is an associate professor in the Department of Medical History and Bioethics at the University of Wisconsin–Madison.