Data & Society

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.

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.

While many people have found benefit and respite in using chatbots for companionship, mental health, and emotional support, the widespread adoption of these tools has also resulted in harm and raised deep concerns about identity and safety. How are chatbots shaping people’s understanding of themselves? What concerns do therapists have about their use? How might these tools be designed and implemented to prioritize users’ wellbeing? What kinds of guardrails, regulations, and safety protocols might be effective?

In connection with Data & Society’s ongoing research on mental health and chatbots, on February 26 we explored these questions and more in a conversation moderated by researchers Livia Garofalo and Briana Vecchione. Together with Luca Belli, AI safety lead at Spring Health; Miranda Bogen, founding director of the AI Governance Lab at the Center for Democracy & Technology; and psychiatrist and psychotherapist Marlynn Wei, they discussed the profound shifts in how people seek help and support, and how mental health professionals, policymakers, and tech designers are navigating these shifts now.

Learn more about the event and Data & Society’s research on mental health chatbot interventions.

In her new report (404) Job Not Found: What Workforce Training Can’t Fix for Black Atlantans in the Age of AI, Data & Society researcher Anuli Akanegbu provides the first ethnographic examination of how AI-related skills are defined, taught, and valued across Atlanta’s growing tech economy. Drawing on interviews, field observations, and historical analysis, she traces how AI literacy is promoted by industry, implemented by government, and interpreted by workers and community leaders navigating an increasingly AI-driven workforce infrastructure.

On February 17, Akanegbu, TechEquity Senior Vice President of Labor Programs Tim Newman, and Bard Computer Science Professor Annabel Rothschild held a critical conversation on the policy stakes of AI-focused workforce development at the state and national level. This conversation was  Informed by Akanegbu’s report and an accompanying policy brief co-authored by D&S Policy Manager Serena Oduro, who moderated this conversation, panelists discussed how government and industry priorities shape workers’ access to opportunity and how policy can address the real-world impacts of automation and AI on workers.

Learn more about the event

Read Anuli's report

Learn about Data & Society's 'AI Civics' Initiative

The second Trump administration has launched a full-scale effort to achieve “unchallenged global technological dominance.” It is accelerating the construction of AI infrastructure, from opening up federal lands to ramping up energy production. It has invoked AI-enabled “efficiency” in order to replace federal workers, removed agency guidance on algorithmic discrimination,  and supercharged the use of AI in areas including defense and immigration enforcement. The administration has also pursued novel public ownership efforts, such as taking equity  in Intel and critical minerals firms. To what end? Officials say they are now maximizing the “export of the American AI technology stack.” This is not the deregulatory tech agenda predicted by both supporters and critics of President Trump. So what is it?

How should we understand the administration’s actions when it comes to AI? What dynamics are driving these changes in AI policymaking? What might be the downstream consequences for Americans? And how should we respond?

Generative AI models are marketed as the next revolution in workplace automation, but they ultimately rely on human labor — from the people labeling content and checking outputs, to the content creators and workers whose data are extracted to build the systems. As management and organizational leaders adopt AI across workplaces, the use of these systems raises questions about how companies are reshaping the quality of work, job security, and the value of  human labor. How are workers’ lives impacted when AI is used to monitor performance, surveil output, or make intrusive management decisions? Will AI disrupt industries and business models? How can we make sure technology supports workers, rather than undermining them?

About 'Understanding AI'

In the fall of 2025, The New York Public Library and Data & Society collaborated to present “Understanding AI,” a four-part live event series exploring the social implications of artificial intelligence and its impacts on democracy, the environment, and human labor. Featuring key figures in the AI ethics field, these events took place at the Stavros Niarchos Foundation Library (SNFL)in New York City as part of the library’s7 Stories Up program, and are now available for all to watch.

Revisit the series

The concentration of power and lack of regulation in the technology industry directly shapes how AI is designed and deployed, and whose interests it serves. That means decisions about these tools often reflect corporate priorities over public benefits. While AI is often held up as a tool to increase “efficiency,” it is essential to ask: efficiency for whom, and at what cost? What would it mean to create and oversee AI in the public’s best interest? How could these technologies be made more accountable to the people and communities they affect? And what is needed to create a future where AI works for everyone?

About 'Understanding AI'

In the fall of 2025, The New York Public Library and Data & Society collaborated to present “Understanding AI,” a four-part live event series exploring the social implications of artificial intelligence and its impacts on democracy, the environment, and human labor. Featuring key figures in the AI ethics field, these events took place at the Stavros Niarchos Foundation Library (SNFL)in New York City as part of the library’s7 Stories Up program, and are now available for all to watch.

Revisit the series

Artificial intelligence technologies run on powerful computers that require vast amounts of energy, water, and critical minerals. As AI use grows, so does its environmental footprint. Yet there is little consensus on how to assess and address the technology’s toll on the climate before irreparable damage is done. How can we understand the impact AI data centers have on communities and the environment? How can we ensure that communities are able to use empirical data about those impacts to fight back?

About 'Understanding AI'

In the fall of 2025, The New York Public Library and Data & Society collaborated to present “Understanding AI,” a four-part live event series exploring the social implications of artificial intelligence and its impacts on democracy, the environment, and human labor. Featuring key figures in the AI ethics field, these events took place at the Stavros Niarchos Foundation Library (SNFL)in New York City as part of the library’s7 Stories Up program, and are now available for all to watch.

Revisit the series