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AI and Cultural Production


Dr Pei-Sze Chow and Dr Claudio Celis Bueno


Jorge Caballero Ramos, University Pompeu Fabra of Barcelona              (

Anna Giralt Gris, University Pompeu Fabra of Barcelona (

Frederic Guerrero-Solé, University Pompeu Fabra of Barcelona              (

Ada Popowicz, University of Amsterdam (

Tiziana Lentini, Università per Stranieri Dante Alighieri (

Hiromi Tanaka, Meiji University (

Nanne van Noord, University of Amsterdam (

Aleena Chia, Goldsmiths, University of London (

Paulo Nuno Vicente, Universidade Nova de Lisboa (

Catarina Duff Burnay, Universidade Católica Portuguesa (


In this era of the Fourth Industrial Revolution, Artificial Intelligence (AI) has by now become ubiquitous in our everyday lives, driving technologies and processes in healthcare, transport, security, communications, and beyond. AI-powered technologies are now being used in the cultural and creative industries at various stages of production, both in the creative and artistic dimension and in the business and commercial aspects.

To a certain extent, there is an inherited idea that creativity and creative labour cannot (or should not) become automated, as if these were unique traits of human activity. From this perspective, the deployment of AI in cultural production can be seen by some as undermining the spontaneity and freedom of human actions and creative agency. Other cultural critics prefer to focus on more concrete consequences of this technology, such as its ethical, political, and economic dimensions. From a different perspective, enthusiasts of the technology may not only celebrate its economic and technical benefits, but also argue that the fact that machines can now perform creative tasks in the field of cultural production represents a radical step towards a true artificial intelligence. On the contrary, critics of this phenomenon could contend that this is possible only because of the process of standardization and normalization that the culture industry actually entails. Finally, there are those who suggest that the radical advances in artificial intelligence and algorithmic technologies calls for a redefinition of inherited categories such as those of creativity, originality, culture, etc.

Despite the multiple perspectives and approaches to the topic, what is becoming evident are not only its urgency and complexities, but also the need for interdisciplinary research. How should we as scholars in the humanities and social sciences respond to and engage with a technological development that is now inserting itself into our fields of inquiry and creative practices? How can we engage with the practitioners building creative AI tools to address issues of trust, agency, bias, and fairness?

In this group we seek to understand the social, aesthetic, economic, and political consequences of this phenomenon while forging connections between researchers from different disciplines as we explore new perspectives, approaches, and methods for the study of AI in cultural production.

Between February 2023 and February 2024 Pei-Sze Chow and Claudio Celis Bueno will work on the project 'Automated Cinema: Technographic Explorations of Artificial Intelligence in Film Culture' at the Institute for Advance Study ( Other activities of the research group include a reading group and an interdisciplinary seminar series (2023).


Title: ‘Interdisciplinary Perspectives on AI & Culture: Art and Science In Conversation’ (Spring 2023)

Description: An interdisciplinary seminar series focused on bringing humanities scholars and computer scientists to the table to exchange critical perspectives on the intersections between AI and culture. Across four sessions, the series aims to identify gaps in how different disciplines conceptualize AI in culture and culture in AI. We aim to find a common language as a first step towards establishing interdisciplinary collaboration. The speakers represent diverse sections in UvA, including history, philosophy, film and media studies, cultural studies, complex systems, multimedia analytics, and machine learning.


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