The Critical AI Seminar series continues in 2025 and 2026 with another four lectures that critically address Artificial Intelligence (AI) from various perspectives – across different contexts of application and through different lenses of critique. With these lectures we hope to once again bring together scholars from around the world in engaging discussions and further contribute to Critical AI Studies as a continuing ‘field in formation’ (Raley and Rhee, 2023).

The seminars are online, open to everyone. For each seminar, one or two prominent invited speaker(s) are invited to give a talk that engages theoretically or empirically with AI.

The seminar series is organised by Anna Schjøtt Hansen, Dieuwertje Luitse and Tobias Blanke, who are part of the Critical Data & AI Research Group at the University of Amsterdam. It is supported by the University of Amsterdam’s Research Priority area Human(e) AI, the Deep Culture Project, and the Amsterdam School for Cultural Analysis, and is hosted by Creative Amsterdam (CREATE). 

Upcoming seminars  

November 12, 5-6:30 PM (CEST): Invited talk by Louise Amoore and Alexander Campolo, ‘On reading machine learning‘

Registration here

One of the strengths of Critical AI studies has been a rapid development of methods for addressing the different social and political objects that encompass AI. We now have outstanding studies of datasets, material infrastructures, ecologies, histories, and the political economy of platforms. Rather than naively “reading” model outputs, they account for their conditions of possibility. These studies cut through words—ideologies ranging from hype to doom—to grasp the interplay of interests, materiality, and power that constitute AI. In this talk, we will reflect on the characteristics of this literature, its distinctive tropes, style, and conventions. We then propose critical reading strategies for scholars in the interpretive social sciences and humanities, who, in their own way, face the problem of reading texts for whom they are not the intended audience.

Louise Amoore is Professor of political geography and Director of the Leverhulme Centre for Algorithmic Life, Durham University. Her work addresses the politics of machine learning algorithms and the epistemologies of contemporary AI. She is the author of Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (2020) and The Politics of Possibility (2013), both with Duke University Press. Louise is Fellow of the British Academy.

Alexander Campolo is a postdoctoral researcher on the “Algorithmic Societies” project in the Department of Geography at Durham University. His work draws from the history of science and technology and social theory to explore the epistemological and political implications of machine learning. He received his PhD from New York University and has previously worked as a postdoctoral fellow at the Institute on the Formation of Knowledge at the University of Chicago and the AI Now Institute.