Public lecture

AI & Cultural Heritage

  • 28 March 2022 - 28 March 2022
  • 11:00 am - 4:00 pm
  • Virtual IAS

As part of the IAS Annual Theme 'AI:Facts, Fictions, Futures', this virtual event will bring together a range of academics to discuss AI & Cultural Heritage.

The role and impact of AI is not limited to the scientific area; it also has enormous significance for society and culture. In the course of this event, our Fellows and invited speakers consider applications of AI and digital technology in the GLAM (Galleries, Libraries, Archives, and Museums) sector, examining the collection, analysis, and dissemination of cultural heritage data, how this information might be experienced, and the ethical issues raised by these processes.




Introductory Remarks

Rachel Grew, Lise Jaillant, Amalia Sabiescu, Marsha Meskimmon


AI Technologies and Emerging Museum Practices

Oonagh Murphy


Break for lunch


Closing the Loop Between ML Research and Library Systems

Ryan Cordell


AI and Art, from the Micro Level to the Macro Level

Ahmed Elgammal


AI & Cultural Heritage Roundtable

Claire Warwick, Chao Tayiana Maina, Ahmed Elgammal, Kathryn Brown, Guzden Varinlioglu, Victoria Lemieux


EyCon Team: Visual AI and Early Conflict Photography

Dr Julien Schuh (Nanterre University of Paris), Daniel Foliard (University Paris Cité)  and Dr Lise Jaillant (Loughborough University)


When Public Data Shouldn’t Be Public: The Ethics of using AI on Archival Corpora

Victoria Lemieux


Concluding remarks and close

Ooonagh Murphy, Goldsmiths

AI Technologies and Emerging Museum Practices

Museums are by their very nature data centric institutions, they are collectors and creators of a diverse range of data - be that the bone density of a dinosaur, the market value of an artwork, the most viewed collection item on their website, or how long visitors spend in a particular gallery.  These datasets and the ethical and legal frameworks that govern them are complex, a complexity that is in part, drawn out of the differing motivations and rationales for the collection and creation of these data sets. From reporting to funders, to developing new insights into audiences, and gaining deeper understanding of collections. The data collected, processed, and held in museums today is rich and varied in its intent. 

Ryan Cordell, University of Illinois 

Closing the Loop Between ML Research and Library Systems

Drawing on the “Machine Learning + Libraries” report written for the Library of Congress, Cordell will argue that for libraries to lead broader machine learning (ML) conversations, we must narrow the gap separating promises that ML will enhance discoverability for library materials—such as can be found in ML research or grant proposals—and the library systems through which most users encounter those materials. While ML projects often promise to enhance collection metadata, illuminate new connections between holdings, or generate alternative user interfaces for navigating collections, in practice ML projects rarely close the loop between research data and library systems.

Even when working with library data, ML researchers often publish their results for disciplinary audiences and their data in separate repositories, where few other users of those library collections are likely to encounter them. Likewise, library professionals are hesitant to incorporate probabilistic ML data directly into discovery systems alongside metadata compiled by catalogers and other information professionals. In other words, even as ML methods have grown more powerful, nuanced, and sophisticated, ambitious hopes that ML might help better identify and describe vast library collections have been largely unmet, at least from the perspective of library patrons, researchers, and students. Developing more iterative, experimental, and even speculative interfaces that allow users to explore collections through ML-derived patterns can enhance library data while educating users about ML processes, decisions, and biases.

Ahmad Elgammal, Rutgers University

AI and Art, from the Micro Level to the Macro Level

In this talk, Elgammal will present results of recent research activities at the Art and Artificial Intelligence Laboratory at Rutgers University. We investigate perceptual and cognitive tasks related to understanding human creativity in visual art. In particular, we study problems related to art styles, influence, and iconography. We develop computational models that aim at providing answers to questions about what characterizes the sequence and evolution of changes in style over time. He will talk about how AI can help analyze art in new ways, at the micro level and macro level.

Claire Warwick, Chao Tayiana Maina, Ahmed Elgammal, Kathryn Brown, Guzden Varinlioglu, Victoria Lemieux

AI & Cultural Heritage Roundtable

The use of AI and digital technologies has the power to dramatically transform the nature of the cultural heritage sector; not just in terms of the information found and conveyed to the viewer or visitor, but how that knowledge is experienced. This roundtable discussion considers what the most significant challenges and developments might be in this field, and how might AI shift the experience, the very landscape of cultural heritage?

The participants in the roundtable represent a wide range of different fields within this sector. Dr Kathryn Brown (Loughborough University, UK) is an art historian interested in the intersection of museums, art markets, and digital art history. Dr Ahmed Elgammal (Rutgers, USA) is a computer scientist who founded and directs the Art and Artificial Intelligence Laboratory, examining data science in the digital humanities. Dr Victoria Lemieux (University of British Columbia, Canada) is an Associate Professor of archival science, specialising in information management, especially through blockchain technology. Chao Tayiana Maina (African Digital Heritage and the Museum of British Colonialism, Kenya) specialises in digital heritage and her work focuses on how technology may be used to preserve, disseminate, and engage with African heritage. Dr Guzden Varinlioglu (MIT, USA) examines how digital technology may contribute to the preservation and presentation of architectural cultural heritage. Prof Claire Warwick (Durham University, UK) is a professor of digital humanities with a specific interest in how digital resources are used in cultural heritage.

EyCon Team - Dr Julien Schuh (Nanterre University of Paris), Daniel Foliard (University Paris Cité) and Dr Lise Jaillant (Loughborough University)

Visual AI and Early Conflict Photography

Recent digitisation efforts of historical photographs by archival institutions have often been done in silo. This is an issue for researchers and archivists, but it also raises the question of public uses of history when it comes to contemporary perspectives on colonial/imperial warfare. Disconnected visual repositories reinforce deeply entrenched notions of national exceptionalism in France, Britain and in other states with a history of international interventionism and expansionism.

This presentation will provide an overview of the EyCon project. Drawing on advanced technologies such as Artificial Intelligence, EyCon (Early Conflict Photography and Visual AI) aims at connecting, analysing and commenting on these divided repositories to increase the discoverability and usability of overlooked and scattered material on colonial, imperial and international armed conflicts up to 1918. EyCon’s primary objective is to assess the usefulness of computation to visualise, navigate and analyse large visual corpora. The project aims at harnessing and questioning computation as well as testing new approaches to visualisation when it is applied to historical investigation. In doing so, it addresses the ethical and epistemological issues raised by the application of AI tools to controversial pasts

Victoria Lemieux

When Public Data Shouldn’t Be Public: The Ethics of using AI on Archival Corpora

The right to privacy has increasingly come to be about informational privacy, especially in light of persistent technological breakthroughs.  The amount of information capable of being known about each of us remains staggering. In 2015, researchers funded by the World Bank’s Big Data Innovation Challenge undertook an investigation into the relationship between citizen trust in state institutions and social protest that raised questions about individuals’ right to privacy in relation to the secondary use of their data and exploration of large archival corpora. The study, which used mixed-initiative social media visual analytics of approximately 11 million sentiment classified Tweets from the period of the 2014 FIFA World Cup in Brazil, explored

1) how Brazilian citizens felt about their state institutions

2) how these feelings connected to their sentiments about Brazilian Federal and State government and politicians

and 3) how such sentiments translated into collective behaviors, such as social protests.  

In this presentation, I will use this case study, drawing upon the ideas of philosophers such as Martin Heidegger, Michel Foucault, and Luciano Floridi, as a site to explore the secondary use of public archival collections of social media data and its relationship to privacy. I will reflect upon the complex nature of privacy: its nebulous relationship to intimacy, secrecy, trust and anonymity; the notion of a life cycle of privacy; and the role of the individual, the government and the market in protecting privacy.  And, I will explore the policy responses suggested by different schools of thought on the issue of informational privacy and the secondary use of data.

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Kieran Teasdale
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