People

PhD candidate

Bokar N’Diaye is a PhD Candidate on the Deep Culture project. Trained in comparative anthropology of religions and digital humanities at the university of Geneva (Switzerland), his primary interests lie in the combinations of these two methodologies to survey the context of emergence and adoption of generative ML models, as well as the understanding of AI as constituting just as much of a rhetorical (or even mythological) device as it does a state-of-of-art technology. In the application In the context of the Deep Culture, he will explore the mediation of human creativity through AI applications, as well as the way users navigate or rationalize the uncertainty tied to its outputs. He gave presentations in several conferences in the STS or DH field (NeurIPS, 4S, MASSHINE), and is published in Hertziana Studies in Art History.

PhD candidate

Chloe Papadopoulou is a PhD candidate in the Deep Culture project. Her research aims to investigate how deep learning models impact public memory by shaping historical representations and categorizing identities, with a focus on feminist and minority-led narratives. Working primarily with historical archives, she is interested in applying explainability and archival analysis techniques to examine how AI models interact with historical records, towards the development of more context-sensitive, democratic and culturally grounded AI systems. She previously completed her master’s degree in digital Humanities & Digital Knowledge at the University of Bologna, where she engaged in interdisciplinary projects at the intersection of computer science and the humanities, across diverse subjects including clinical and computational linguistics, culture, history, philosophy, social sciences and cinema.

PhD candidate

Louis Ravn is a PhD Candidate on the Deep Culture project at the University of Amsterdam. In this context, his research focuses on the epistemics, politics, and materialities of data and deep learning techniques. His primary research interest lies in better understanding how contemporary deep learning is increasingly shaped by sociotechnical operations of synthesis, compression, and distillation. To that end, he draws from frameworks across science and technology studies (STS), critical AI studies, critical data studies, and social theory. Before joining Deep Culture, he was a Research Assistant at the University of Copenhagen. His research has been published in Big Data & Society, Internet Policy Review, Surveillance & Society, and Digital Society.

PhD candidate

Orsola M. Borrini is a PhD candidate in the HAICu project and works together with the PhD students in the Deep Culture project on historical archives. Her research explores the ethical considerations and practical limitations of Explainable Artificial Intelligence (XAI) applications in Cultural Heritage, with a focus on fostering transparency and accountability in the deployment of these technologies. With a background in (Digital) Humanities, she is a passionate advocate for interdisciplinary approaches. Beyond AI applications in Cultural Heritage, her interests include data-driven historical research, particularly addressing untold stories and contested historical heritage. In the context of Deep Culture, she will investigate the intersection of deep learning and historical archives, where the intricate dynamics between mainstream historiography, divergent narratives and new technologies come into focus.

Bruno Nadalic Sotic is a PhD candidate in the HAICu project and works together with the PhD students in the Deep Culture project on historical archives.

Senior researcher

Julia Noordegraaf is professor of Digital Heritage at the Faculty of Humanities, University of Amsterdam. She founded the research program and lab Creative Amsterdam that studies the history of urban creativity using digital data and methods. Her research focuses on the reuse of digital cultural heritage for historical research, exploring the epistemological and methodological implications of using digital sources and methods. In the context of the European Time Machine project, she coordinates the realization of the Amsterdam Time Machine: a ‘Digital Twin’ for location-based, personalized access to historical information on the city.

Senior researcher

Paula Helm is an Assistant Professor specializing in the fields of Critical AI Studies and Empirical Ethics. Originally trained in Anthropology and Peace and Conflict Research, her work today is situated at the intersection of STS, Media Studies and Empirical Technology Ethics. She is the scientific leader of the Empirical Ethics Research Group at the Amsterdam Institute for Advanced Studies and the coordinator a new Media Studies MA-track on Cultural Data & AI, combining critical thinking with data science. The larger mission of Paula’s work is to move AI-Ethics from the PR- to the Engineering-, Infrastructural- and Development-Level.

Senior researcher

Thomas Poell is Professor of Data, Culture & Institutions at the University of Amsterdam. Leveraging social media data and digital methods, he has studied how the use of digital platforms is affecting the mobilization, organization, and communication of protest around the globe. In recent years, Thomas has examined how platforms and AI are reshaping the cultural industries around the globe. He is the co-author of Platforms and Cultural Production (Polity, 2022) and The Platform Society (Oxford University Press, 2018).