Data & Society

At the turn of the 20th century, the anti-immigration and eugenics movements used data about marginalized people to fuel racial divisions and political violence under the guise of streamlining society toward the future. Today, as the tech industry champions itself as a global leader of progress and innovation, we are falling into the same trap.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. Predatory Data is the first book to draw this direct line between the datafication and prediction techniques of past eugenicists and today’s often violent and extractive “big data” regimes. Torres and Gebru have also extensively studied the second wave of eugenics, identifying a suite of tech-utopian ideologies they call the TESCREAL bundle.Purchase your own copy of Anita Say Chan’s book Predatory Data: Eugenics in Big Tech and Our Fight for an Independent Future: https://bookshop.org/a/14284/9780520402843.Learn more about the event at datasociety.net (https://datasociety.net/events/resisting-predatory-data/).

Two years ago, we were told that ‘prompt engineer’ would be a real job — well, it’s not. Is generative AI actually going to replace and transform human labour, or is this just another shallow marketing narrative?In this episode of Computer Says Maybe, host Alix Dunn speaks with Data & Society researchers Aiha Nguyen and Alexandra Mateescu, authors of the primer 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 traditionally feminized work like caregiving.Further reading:Generative AI and Labor: Power, Hype, and Value at Work by Aiha Nguyen and Alexandra MateescuBlood in the Machine by Brain MerchantAiha Nguyen is the Program Director for the Labor Futures Initiative at Data & Society where she guides research and engagement. She brings a practitioner's perspective to this role having worked for over a decade in community and worker advocacy and organizing. Her research interests lie at the intersection of labor, technology, and urban studies. She is author of The Constant Boss: Work Under Digital Surveillance and co-author of ‘At the Digital Doorstep: How Customers Use Doorbell Cameras to Manage Delivery Workers’, and ‘Generative AI and Labor: Power, Hype and Value at Work’.Alexandra Mateescu is a researcher on the Labor Futures team at the Data & Society Research Institute, where she investigates the impacts of digital surveillance, AI, and algorithmic power within the workplace. As an ethnographer, her past work has led her to explore the role of worker data and its commodification, the intersections of care labor and digital platforms, automation within service industries, and generative AI in creative industries. She is also a 2024-2025 Fellow at the Siegel Family Endowment.Subscribe to our newsletter to get more stuff than just a podcast — we run events and do other work that you will definitely be interested in!

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. To explore these themes, we were joined by Nia Johnson, Ekene Ijeoma, and Lori Regattieri — academics, practitioners, and artists who are each, in their own way, responding to the ways digital infrastructures are transforming the built, natural, and social environments. In a conversation moderated by Trustworthy Infrastructures Program Director Maia Woluchem, we broke down confrontations between technological infrastructures and local communities and discussed how to  reshape narratives of process, power, change, and futurity.This public panel is part of Connective (t)Issues, a Data & Society workshop organized by the Trustworthy Infrastructures program in partnership with Duke Science & Society. Learn more about the workshop at datasociety.net. https://datasociety.net/announcements/2024/11/20/connective-tissues/

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 examined red-teaming’s place in the evolving landscape of genAI evaluation and governance.Our discussion drew on a new report by Data & Society (D&S) and AI Risk and Vulnerability Alliance (ARVA), a nonprofit that aims to empower communities to recognize, diagnose, and manage harmful flaws in AI. The report, Red-Teaming in the Public Interest, investigates how red-teaming methods are being adapted to confront uncertainty about flaws in systems and to encourage public engagement with the evaluation and oversight of genAI systems. Red-teaming offers a flexible approach to uncovering a wide range of problems with genAI models. It also offers new opportunities for incorporating diverse communities into AI governance practices.Ultimately, we hope this report and discussion present a vision of red-teaming as an area of public interest sociotechnical experimentation.Download the report and learn more about the speakers and references at datasociety.net.--00:00 Opening00:12 Welcome and Framing04:48 Panel Introductions09:34 Discussion Overview10:23 Lama Ahmad on The Value of Human Red-Teaming17:37 Tarleton Gillespie on Labor and Content Moderation Antecedents25:03 Briana Vecchione on Participation & Accountability28:25 Camille François on Global Policy and Open-source Infrastructure35:09 Questions and Answers56:39 Final Takeaways

Do you ever wonder how semiconductors (AKA chips) — the things that make up the fine tapestry of modern life — get made? And why does so much chip production bottleneck in Taiwan?Luckily, this is a podcast for nerds like you. Alix was joined this week by Brian Chen from Data & Society, who systematically explains the process of advanced chip manufacture, how its thoroughly entangled in US economic policy, and how Taiwan’s place as the main artery for chips is the product of deep colonial infrastructures.Brian J. Chen is the policy director of Data & Society, leading the organization’s work to shape tech policy. With a background in movement lawyering and legislative and regulatory advocacy, he has worked extensively on issues of economic justice, political economy, and tech governance.Previously, Brian led campaigns to strengthen the labor and employment rights of digital platform workers and other workers in precarious industries. Before that, he led programs to promote democratic accountability in policing, including community oversight over the adoption and use of police technologies.**Subscribe to our newsletter to get more stuff than just a podcast — we run events and do other work that you will definitely be interested in!**

On November 14, in a conversation moderated by Data & Society Senior Researcher Ranjit Singh, Madhumita Murgia and Armin Samii discussed Murgia’s new book, Code Dependent: Living in the Shadow of AI. Together, they explored living with data by describing their journeys into understanding it, reporting on it, and resisting it. While Murgia’s journalistic journey began with tracing the flow of her personal data sold by data brokers, Samii used his expertise as a computer scientist to build UberCheats, an algorithm auditing tool that extracts GPS coordinates from UberEats receipts to calculate the difference between the actual miles a courier traveled and those Uber claimed they did. In Code Dependent, Samii’s story is the focus of a chapter on how data-driven systems come to play the role of the boss.Purchase a copy of Code Dependent: https://bookshop.org/a/14284/9781250867391Learn more at datasociety.net (https://datasociety.net) 

Xiaowei R. Wang and Zara Rahman, both influential speakers, discuss the critical need for interdisciplinary research in understanding technology's societal impacts. Ranjit Singh delves into algorithmic systems and their implications on communities. Michelle Miller addresses the labor force and tech companies, while Alondra Nelson and John Palfrey emphasize the importance of equitable tech governance. Felicia Wong highlights the role of political power in shaping future technology's impact. Together, they advocate for collaborative movement-building to ensure a just technological future.

In the United States, Black maternal health is in steep decline. Despite increased awareness and better data about the depths of racial health disparities, outcomes for Black birthing people remain poor. At the same time, a revolution in healthcare technologies is underway, and as they provide care at the frontlines of a crisis, birth workers are figuring out how to make digital health technologies work for them and their patients.In "Establishing Vigilant Care: Data Infrastructures and the Black Birthing Experience," Joan Mukogosi explores how digital health technologies can produce new forms of harm for Black birthing people — by exposing Black patients to carceral systems, creating information silos that impede interoperability, and failing to meet privacy standards. By paying close attention to how clinical contexts and their associated digital technologies impact how care is delivered, this research offers a glimpse into possibilities for improved cohesion between digital health technologies and birth work.Learn more about Data & Society at datasociety.net.

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.