Artificial Intelligence (AI) is not magic or sentient; it does not even describe one coherent set of technologies. In two new books, Emily M. Bender, Alex Hanna, and Karen Hao explore how AI instead serves as a powerful marketing tool for tech giants who have a product to sell and profits to rake in. On June 6 — in a conversation moderated by Tamara Kneese, director of Data & Society’s Climate, Technology, and Justice program — these authors explored AI’s impact on our environment and society, and the motivations of the tech elite that build and shape it.

On May 6, 2025 at The Greene Space in New York City, Dr. Julián Posada and Aiha Nguyen set the stage for Data & Society’s online workshop “What is Work Worth? Exploring What Generative AI Means for Workers’ Lives and Labor.” Drawing on interviews with Venezuelan data workers as well as peer research and accounts from the field, Dr. Posada’s keynote highlighted three stories that illustrate the socioeconomic conditions enabling generative AI’s development and deployment.

This live fireside chat was co-organized by Data & Society and Tech Workers Coalition during SF Climate Week 2025 at Tamarack, a community space located in Oakland, California. The live discussion features Tamara Kneese in dialogue with tech journalist, Alexis Madrigal, and internet researcher, Xiaowei R. Wang. The speakers reflect on the relationship between current discourses around the environmental impacts and histories of resource extraction across the AI supply chain. How are communities grappling with the material, environmental impacts of digital technologies from an international, historical perspective? How do we build solidarities of understanding between knowledge workers and directly impacted communities?

On April 10th, Anita Say Chan, author of Predatory Data: Eugenics in Big Tech and Our Fight for an Independent Future (UCP 2025 and open access), joined Émile P. Torres and Timnit Gebru for a discussion of the 21st century eugenics revival in big tech and how to resist it in a conversation moderated by Trustworthy Infrastructures Program Director Maia Woluchem.

In this episode of Computer Says Maybe, host Alix Dunn speaks with Data & Society Labor Futures researchers Aiha Nguyen and Alexandra Mateescu, who recently authored Generative AI and Labor: Power, Hype, and Value at Work. They discuss how automation is now being used as a threat against workers, and how certain types of labor are being devalued by AI — especially (shocking) traditionally feminised work, such as caregiving.

Physical and digital infrastructures have raised tensions around the world, seeding land disputes, climate effects, and disrupting social fabrics. Yet they are also intertwined with myths of progress, transformation, and speculation. What does this friction reveal? How can the stories we tell about infrastructures illuminate problems and lead us toward solutions? What do these stories say about where power lies and how it shifts? How might they help surface connections across nations, communities, and cultures?

What exactly is generative AI (genAI) red-teaming, what strategies and standards should guide its implementation, and how can it protect the public interest? In this conversation, Lama Ahmad, Camille François, Tarleton Gillespie, Briana Vecchione, and Borhane Blili-Hamelin examine red-teaming’s place in the evolving landscape of genAI evaluation and governance.

In time for this year’s RightsCon, Data & Society Policy Director Brian J. Chen joins Alix Dunn of Computer Says Maybe for a conversation about the process of advanced chip manufacture, its entanglement with US economic policy, and the colonial making of Taiwan’s chip supremacy.

Code Dependent spans stories from across the globe and calls attention to the voices of ordinary people as they navigate the everyday challenges of living with data-driven systems and work to reclaim their agency. In the process, author Madhumita Murgia invites a deeper reflection on these systems and how they interact with human ethics and judgment. Learn more in this Data & Society Network Book Forum.

Foreseeable Futures, held on September 26, 2024, was a celebration of Data & Society at 10, where we celebrated our first decade with our incredible network of alumni, friends, and supporters.

In this Databite discussion, Mukogosi spoke with Dr. Mary Fleming and Ijeoma Uche about the facts and future of data-driven maternal care for Black patients. Reckoning with the decline of Black maternal health amid advancements in clinical technologies, they discussed the implications of an increasingly data-driven response to the Black maternal health crisis.

The Formalization of Social Precarities podcast explores platformization from the point of view of precarious gig workers in the Majority World. This conversation was moderated by Aiha Nguyen and Murali Shanmugavelan featuring the voices of Ambika Tandon, Ludmilla Costhek Abílio, and Ananya Raihan. You will also be hearing the experience of two platform workers interviewed for this project: Fatema Begum from Bangladesh and Nicolas Sauza from Brazil. Their voices are narrated in English by Data & Society staff members Iretiolu Akinrinade and Rigoberto Lara Guzmán, respectively. This podcast was edited by Sam Grant.

Data & Society’s report, Doing the Work: Therapeutic Labor, Teletherapy, and the Platformization of Mental Health Care, written by Livia Garofalo, explores how these new arrangements of therapeutic labor are affecting how therapists provide care and make a living in the US. By focusing on the experiences of providers who practice teletherapy and work for digital platforms, our research examines the fundamental tensions that emerge when a profession rooted in clinical expertise, licensing, and training standards meets the dynamics of platformization, productivity incentives, and algorithmic management. In this conversation, we reflected on how technology is changing the conditions of how therapists do their work, on the consequences for the present and future of therapeutic labor, and on how this might be changing our understanding of therapy itself.

Predominant narratives that cast workers as replaceable hide the ways in which workers are actively responding to generative AI. Many build new skills and tools to their advantage while others sabotage, counteract and otherwise circumvent these systems. The relationship workers have with technology is much more dynamic, contested and layered. Narratives that cast workers as replaceable, for example, obscure the active and complex ways that workers are responding to generative AI. While many build new skills and use these tools and systems to their advantage, others sabotage, counteract, and otherwise circumvent them. In this conversation, Livia Garofalo, Jeff Freitas, Quinten Steenhuis and Data & Society host Aiha Nguyen explored the ways that workers reshape their relationship with generative AI tools – and as a result, with work itself.

In a conversation moderated by D&S Principal Researcher Sareeta Amrute, panelists Chelsea Peterson-Salahuddin, Irene Solaiman, and Jason D’Cruz discussed how practitioners, theorists, and community members approach the fraught issue of trust inside and outside institutions. Together, they considered how legacies of racism, dehumanization, refusal, and opacity inform trust — how it operates, and fails to operate, in data-centric spaces. They also discussed trust’s typical framing as a normative construct, as well as the meaning of mistrust and its consequences for vulnerable communities.

Queer people have long been rendered invisible by data systems: survey questions that impose gendered binaries, inquiries that dismiss queer subjects as unimportant or insignificant, and ahistorical erasures of queer life that push queer experiences and knowledge further into the margins. Yet visibility also comes with risk. Digital and biomedical surveillance, personal data breaches, and privacy concerns arise when indications of queerness, real or otherwise, are present and unprotected in datasets. The threat imposed by interlocking systems of anti-queer violence and oppression seeds movements away from visibility and towards fugitive tactics of refusal — a kind of strategic invisibility. On February 15 in a conversation moderated by Data & Society Research Analyst Joan Mukogosi, Nikita Shepard and Harris Kornstein discussed this problem of data in/visibility as they explore it in their contributions to Queer Data Studies, an anthology edited by Patrick Keilty featuring essays that examine, from a range of disciplinary approaches, how data impacts queer subjects. Together, Shepard, Kornstein, and Keilty broke down the dichotomy between visibility and opacity of queer subjects in data, and engaged in the generative practice of thinking about data from and through queerness.

In labor parlance, “recognition” is the pathway by which workers become a union. In what other ways can we recognize the value of work — beyond the form it takes? With artists and models finding that generative AI reduces them to their image, their words on a page, notes in a song, and even their measurements, how does this emerging technology diminish the value of workers and their contributions, and how might we recognize it? In this discussion, Enongo Lumumba-Kasongo, Şerife (Sherry) Wong, Sara Ziff, and Aiha Nguyen pry open the black box of generative AI and consider what is lost or appropriated in the process of extraction.

Developers claim generative AI will have sweeping impacts that transform work as we know it, creating new opportunities for workers and unleashing dramatic waves of creativity. But this technology will not affect everyone equally: Societal biases and embedded hierarchies that inform who and what type of work is valuable will also influence how generative AI is rolled out and who benefits from it. In this first conversation of a three part series, John Lopez, Milagros Miceli, and Russell Brandom join Data & Society's Labor Futures Program Director Aiha Nguyen to interrogate these layers of issues around Generative AI technology; consider how it scaffolds on previous economic models, structures, and modes of employment; and explore its impacts on workers across the globe.

When people die, they leave behind not only physical belongings, but digital ones. While they might have had specific wishes for what happens to their online profiles and accounts after their deaths, preserving these digital remains is complex and requires specialized forms of care. Because digital remains are attached to corporate platforms — which have control over what online legacies look like and how long they continue — people’s digital afterlives are not necessarily the ones they would have chosen for themselves. On November 16, Tamara Kneese and Tonia Sutherland came together for a conversation about their books, which both foreground death as a site for understanding the social values and power dynamics of our contemporary, platform-saturated world. The conversation between these two authors was moderated by Tamara K. Nopper, senior researcher with Data & Society’s Labor Futures program. Together, they explored death as a site of contestation and transformation.

On October 30, the White House issued its long-awaited executive order on artificial intelligence. We’re heartened by the order’s focus on some of AI’s most pressing real-world harms, and especially encouraged by its commitment to apply mandatory rights-protecting practices to the federal government’s use of AI, drawing heavily from the Blueprint for an AI Bill of Rights. A key issue now will be implementing the order’s directives, and addressing the need to put money and people quickly into action across the federal government to advance a very ambitious plan on a short timeline. Our November 7 at 11 a.m. ET during a special LinkedIn Live event featured analysis of the AI executive order with Data & Society’s Executive Director Janet Haven, Policy Director Brian Chen and two coauthors of the Blueprint for an AI Bill of Rights: D&S Senior Policy Fellow Sorelle Friedler and Brown University Professor and D&S Board Member Suresh Venkatasubramanian. They offered their impressions of the order, considered the implications of guidance from the Office of Management and Budget, and reflected on what’s next for policy and the field.