The project makes reference to 'The Next Documenta Should Be Curated by an Artist' (e-flux, 2003) - which questioned the structures of the art world and the privileged position of curators within it – and extends this questioning to machines. Under this overarching concept, two parallel experiments have been realised to date, applying various machine learning techniques (a subset of AI) to ‘curate’ datasets derived from various biennial exhibitions.

Experiment B³(NSCAM) is a collaboration with artists Ubermorgen, commissioned by The Whitney Museum of American Art for its online platform artport and Liverpool Biennial. It uses datasets from the two commissioning institutions, amongst others, archival curatorial statements, artists names and biographies from past editions. Processing datasets linguistically and semiotically, the AI algorithms ‘learn’ their style and content, calculating a future probability for words to appear, cutting and mixing them together, to generate endless combinations of possible instances of Biennials in flux.

A parallel experiment, AI-TNB is a collaboration with Eva Cetinić and MetaObjects with Sui, exploring human-machine co-authorship. It uses data from Liverpool Biennial 2021 – the photographic documentation of artworks, their titles and descriptions – and applies Open AI’s ‘deep learning’ model CLIP to generate new interpretations of, and connections between, works and texts. As visitors navigate the project, they create their own paths through the material, each journey becoming a co-curated human-machine online iteration of the Biennial saved to the project’s public repository.


Credits:
Series curator – Joasia Krysa
Series technical concept – Leonardo Impett
Series website – Yehwan Song

Experiment B³(NSCAM) is a collaboration with artists Ubermorgen, 2021. Commissioned by The Whitney Museum of American Art for its online portal artport and Liverpool Biennial. https://whitney.org/exhibitions/the-next-biennial

Experiment AI-TNB is a collaboration with Eva Cetinić (experiment machine learning concept and implementation), MetaObjects (Ashley Lee Wong and Andrew Crowe) and Sui (web development and design), 2021. Commissioned by Liverpool Biennial, funded by the UK’s Arts and Humanities Research Council (AHRC) programme Towards a National Collection under grant AH/V015478/1. https://ai.biennial.com/

For a larger discussion on AI and curating, see Liverpool Biennial’s journal Stages vol 9/2021, edited by Joasia Krysa and Manuela Moscoso.https://www.biennial.com/journal/issue-9

Newly Formed is an experiment that combines the art collection of Helsinki Art Museum HAM and multimodal machine learning technology. It is commissioned in the context of Helsinki Biennial 2023 and developed as a collaboration between artist Yehwan Song, Digital Visual Studies project at the University of Zurich, and curator Joasia Krysa, Newly Formed is an AI-driven website where users visit an online map of the city and can interact with the public art collection based on geolocations. Through the map, the user starts to see the city through the collection, moving from one panorama to another through portals, from which they can explore new groupings based on metrics created by the machine. New entanglements emerge from the combined agencies of the model, the visitors, the collection, and the city. In this sense, the AI Entity behind the Newly Formed, facilitates new interpretations, understandings and public presentations of HAM collection, adding a new narrative layer to Helsinki Biennial 2023, working together with the human curators of this edition.