Contemporary art institutions, much like cultural heritage museums around the world, face a process of deep transformation through digitalisation, except that for contemporary art institutions such a process ventures into the material foundations of the artworks themselves: digital technology has become a creative medium for artists, while most recently, Artificial Intelligence, especially machine learning (ML), has started featuring in the production of new artworks.
As a creative medium, ML deeply challenges the limits of knowledge and expertise traditionally held by curators and cultural institutions working with contemporary culture. Although ML has had a transformational impact on the corporate world, the cultural sector is still in need of acquiring adequate media literacy to engage with this technology. Curators and cultural institutions often struggle to understand the technology’s functioning and its creative capacity, holding cultural actors back from much needed engagement.
Our workshop on Wednesday, 11 December explored various technical aspects and types of deep learning and looked into the computational techniques that areincreasingly being used by artists, museums and galleries. The small event was casual to allow cultural researchers as well as gallerists and curators to ask everything they wanted to know about neural nets but were afraid to ask, while giving academic and technical experts a chance to step into wider debates about the way these technologies are used in the art world.
Hosted by Eva Jäger (Serpentine) and Mercedes Bunz (DDH/KCL) with help of the excellent experts Daniel Chavez Heras (KCL) and Leonardo Impett (Bibliotheca Hertziana).
The workshop is part of a series organised by the Creative AI lab founded by the Serpentine Galleries in collaboration with the Department of Digital Humanities, KCL and led by Eva Jäger and Mercedes Bunz.