Visit datasociety.net for to learn more about this Book Talk's speakers, access resources and referenced materials, and to purchase copies of The AI Con and Empire of AI.

Purchase copies of these books from our Bookshop:

• The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want by Emily M. Bender and Alex Hanna
• Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI by Karen Hao

Recorded on May 6, 2025 at The Greene Space in NYC 

Featuring Dr. Julián Posada and Aiha Nguyen 

Resources and recordings are available here: https://datasociety.net/events/what-is-work-worth/

Books

Death Glitch: How Techno-Solutionism Fails Us in This Life and Beyond (Tamara Kneese)

The Pacific Circuit: A Globalized Account of the Battle for the Soul of an American City (Alexis Madrigal)

Blockchain Chicken Farm: And Other Stories of Tech in China's Countryside (Xiaowei Wang)

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 Mateescu
• Blood in the Machine by Brain Merchant

Aiha 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.

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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.

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00:00 Opening

00:12 Welcome and Framing

04:48 Panel Introductions

09:34 Discussion Overview

10:23 Lama Ahmad on The Value of Human Red-Teaming

17:37 Tarleton Gillespie on Labor and Content Moderation Antecedents

25:03 Briana Vecchione on Participation & Accountability

28:25 Camille François on Global Policy and Open-source Infrastructure

35:09 Questions and Answers

56:39 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/14284/9781250867391

Learn more at datasociety.net (https://datasociety.net)

When Data & Society was founded ten years ago, it was rooted in the insight that data-centric technologies have broad and often unseen impacts on society — and that to better understand those impacts and realize technologies that reflect our highest values, we need interdisciplinary, empirical research.

Today, the urgency of that vision is palpable: How societies choose to design and govern technology will determine our collective future. On September 26, we celebrated our first decade with our incredible network of alumni, friends, and supporters. Along with reflections from Data & Society Executive Director Janet Haven, Board President Charlton McIlwain, and Founder danah boyd, the program included a panel discussion and lightning talks.

00:00 Opening
00:10 Welcome | Charlton McIlwain, Board President
08:23 Creating a Field | danah boyd, Founder
19:37 Lightning Talk: Xiaowei R. Wang
27:02 Lightning Talk: Ranjit Singh
33:09 Lightning Talk: Zara Rahman
38:42 Lightning Talk: Michelle Miller
46:00 Acting on What We Know | Alondra Nelson, John Palfrey, Felicia Wong (moderator: Suresh Venkatasubramanian)
1:13:47 Creating Our Future | Janet Haven, Executive Director
1:25:42 Closing | Charlton McIlwain, Board President