Big Data & Society (Sage Journals)

🚨 New in Big Data & Society 🚨 "Contesting data power at the margins" by Ngai Keung Chan et al. https://lnkd.in/gjzizhiZ Examines how Hong Kong activists use data imaginaries to challenge surveillance, develop counter-strategies, and mobilize under datafied control.

🚨 New in Big Data & Society 🚨 "China as an analytical lens for AI and society" by Chuncheng Liu & Zhifan Luo https://lnkd.in/gPeNyp-t Offers a four-part framework using “China” to rethink AI, political economy, and global entanglements in critical AI studies.

🚨 New in Big Data & Society 🚨 "The platformisation tree in China's AI data annotation ecosystem" by Bingqing Xia & Tongyu Wu https://lnkd.in/gb_HfaKR Uses the “platformisation tree” to examine how disability, precarity, and platform labor intersect in China's AI data annotation economy.

🚨 New in Big Data & Society 🚨 "Cosine capital: Large language models and the embedding of all things" by Mikael Brunila https://lnkd.in/gDcHtufK Proposes “cosine capital” to describe how LLM embeddings commodify language and data, reshaping power, abstraction, and AI economies.

🤖 AI Controversies: Democratic Debate — or Authoritarian Reinforcement? New in Big Data & Society “On the controversiality of AI: The controversy is not the situation” by Noortje Marres, Christian Katzenbach, Anders Kristian Munk, and Anna Jobin Public debates about AI are everywhere — from ethics panels to online outrage. But do these controversies actually shape how AI enters society, or do they serve other purposes? This Special Issue introduction argues that AI marks a turning point: rather than opening democratic spaces, AI controversies often reassert expert authority and obscure underlying societal tensions. 🧭 Key Contributions: The authors identify four ways AI controversies interact with real social situations: 1️⃣ Concealing the situation – Debate becomes spectacle, hiding structural issues. 2️⃣ Articulating the situation – Controversy gives voice to social concerns. 3️⃣ Situation articulates the controversy – Social realities drive the debate. 4️⃣ Mutual irrelevance – Hype and lived experience simply don’t meet. ⚠️ Central Question: Are AI controversies a force for democracy — or a stage for techno-scientific authority? This piece challenges us to rethink how we analyse AI debates, urging new methods that confront power, expertise, and public voice. 📖 Read here: https://lnkd.in/eGUgQuvP #AIControversy #TechGovernance #BigDataAndSociety #STS #AIethics

✨ New article alert: "Towards synthetic data justice for development" ✨ 🔍: The paper presents a case study of synthetic datasets being used in the anti-trafficking sector. Mobilizing a data justice lens, I ask: how do synthetic data relate to questions of political economy, (in)visibility, disengagement, and non-discrimination in development contexts? Most importantly, the analysis shows that synthetic data remain steeped in power asymmetries, including the political economy of "data for development" (D4D) and the visibilization of marginalized communities. This highlights the risk of "synthetic-washing" in development contexts, where a faith in the presumed safety of synthetic data obscures their entanglement with longer genealogies of power asymmetry. 🔓: https://lnkd.in/dMmzRx9U 📖: This paper is part of a highly urgent special theme on Datafied Development, which I encourage you to explore: https://lnkd.in/dUcFNt2Z This article is greatly indebted to the editorial guidance and encouragement of Mohammad Amir Anwar and Nanna Thylstrup, thank you very much. Moreover, this research has hugely benefited from early feedback provided by the DALOSS team: thank you Esmée C., Katie Mackinnon, Frederik Schade. I also thank the participants of the “Synthetic data: provocations and frictions of emerging data regimes” workshop at the University of Copenhagen in October 2024 for comments on an earlier version of this paper. Particular thanks go to Tanja Wiehn and Ekaterina Pashevich. In addition, this paper has hugely benefitted from the three anonymous reviewers’ brilliant comments as well as the journal editors’ remarks. Finally, I express my sincere gratitude to my interviewees who were willing to share their insights. #syntheticdata #datajustice #datafordevelopment #antitrafficking

Do public controversies about artificial intelligence (AI) matter? Can they really make a difference to how AI is taken up in society? I am very happy to see our editorial "On the controversiality of AI: The controversy is not the situation" to a special issue on AI controversies published in Big Data & Society published: https://lnkd.in/eCC8XmgZ Led by Noortje Marres, and co-authored with Anders Kristian Munk and Anna Jobin, this piece encapsulates much of our thinking on the role of controversies in the shaping of AI and society in these critical times. It is also important to me, because it summarises some of the key challenges we struggled with in the project "Shaping 21st Century AI – Controversies and Closure in Media, Policy, and Research" (https://lnkd.in/eVTTBRx9) "In public debates as well as in scholarly work, it is often assumed that controversies articulate wider situations out there in the world. But this is not necessarily the case. When it comes to AI, industry discourse and technology enthusiasts increasingly occupy even the spaces of AI critique by sparking controversies on so-called ‘existential risks’, in ways that may conceal rather than elucidate the actual social and political situations in which we find ourselves, as AI is imposed on seemingly all domains and sectors of society. The controversy is not the situation." The full special issue includes articles by Pauline Gourlet, Donato Ricci, Maxime CREPEL, Mona Sloane, Guillaume Dandurand, Fenwick McKelvey, Jonathan Roberge, Tommy Shaffer Shane, Mathieu Jacomy, Matilde Ficozzi, Torben Elgaard Jensen, Laura Liebig, Licinia Güttel, Martin Tironi, Camila Albornoz and Lucy Suchman. https://lnkd.in/eEKtm-6c Thanks to @Sachil Singh, Matthew Zook and Natalia Orrego Tapia at Big Data & Society (Sage Journals) for the patience and the editorial work!

Do controversies about AI matter? Can they really make a difference to whether and how AI is imposed on society? The introduction to our Special Issue on Artificial Intelligence Controversies has now been published in Big Data & Society. https://lnkd.in/ePT944dp Co-authored with Christian Katzenbach, Anders Kristian Munk and Anna Jobin, the essay argues that AI controversies present a watershed moment for public controversies about technoscience. Historically, such controversies have been valued as forces of democratisation, but in the case of AI controversy often operates as an "engine of authority," consolidating hierarchical relations between insiders and outsiders and closing down the space for public debate.   For this reason, it is tempting to conclude that "AI" is the shore on which late 20th century visions of technoscientific democracy have come to die. However, as the research articles and commentaries in our Special Issue show, the last decade of AI controversy has equally been defined by significant and successful interventions by activists, experts, journalists and everyday publics demonstrating the situated impacts and implications of AI in society.   To understand the changing role of AI controversies in society and democracy at the current juncture, we therefore need to "broaden the frame" (Suchman, 2020) in controversy analysis. We should examine the relations between AI controversies and the situations — tensions, disputes and frictions in society— to which these controversies are relevant, or alleged to be relevant.   With stellar articles and commentaries by Pauline Gourlet, Donato Ricci, Maxime CREPEL, Mona Sloane, Guillaume Dandurand, Fenwick McKelvey, Jonathan Roberge, Tommy Shaffer Shane, Mathieu Jacomy, Matilde Ficozzi, Torben Elgaard Jensen, Laura Liebig, Licinia Güttel, Martin Tironi, Camila Albornoz and Lucy Suchman. See the complete list of contributions here: https://lnkd.in/eCGnDtwh With special thanks to Sachil Singh, Matthew Zook and Natalia Orrego Tapia at Big Data & Society (Sage Journals)

🧪 Synthetic Data Meets Development: Justice or “Synthetic-Washing”? New in Big Data & Society: “Towards synthetic data justice for development: A case study of synthetic datasets on human trafficking” by Louis Ravn Synthetic data is increasingly promoted as a privacy-safe solution for working with sensitive issues—such as human trafficking. But does it truly eliminate harm, or does it risk masking deeper inequalities? This paper investigates the UN–Microsoft collaboration that produced the Global Synthetic Datasets (GSDs) on human trafficking—now representing over 222,000 simulated survivor profiles. Through a justice lens, the article raises critical questions: Political Economy: Who controls synthetic datasets, and who benefits? (In)Visibility: Can synthetic data make marginalized groups visible without deep misrepresentation? Abstraction vs. Experience: What is lost when trauma becomes “synthetic”? “Synthetic-Washing”: The danger that privacy claims may obscure enduring power asymmetries. Ravn calls for a framework of synthetic data justice—one that goes beyond technical fixes to address ethical, political, and social realities in development contexts. 👉 Read the article: https://lnkd.in/ej74DeA4

In Big Data & Society (Sage Journals), D&S researcher Briana Vecchione, Ph.D. and program director Ranjit Singh consider how the growing adoption of AI in mental health support impacts both users and providers, and advocate for a critical approach to its development and governance. “While chatbots offer the potential benefits of accessibility and personalized responses that resemble human conversation, it is crucial to question the limitations of their reliance on predictive modeling as it relates to their capacity for deep empathy and nuanced care,” they write. https://lnkd.in/eiYCp9Rf