Espositori 2021


Zizi - Queering the Dataset

Zizi - Queering the Dataset

Zizi - Queering the Dataset aims to tackle the lack of representation and diversity in the training datasets often used by facial recognition systems. The video was made by disrupting and re-training these systems, adding drag and gender fluid faces found online, causing the neural network weights to shift from normative identities into a space of queerness. The artwork is a celebration of difference and ambiguity, which invites us to reflect on bias in our data driven society, while exploring what AI can teach us about drag, and what drag can teach us about AI. Originally commissioned by Experiential AI at Edinburgh Futures Institute.




Zizi - Queering the Dataset

Jake Elwes

Jake Elwes is an artist living and working in London. His recent works have looked at machine learning and artificial intelligence research, exploring the code, philosophy and ethics behind it. In his art Jake engages with both the history and tropes of fine art and the possibilities and consequences of digital technology.
Jake's work has been exhibited in museums and galleries internationally, including the ZKM, Karlsruhe, Germany; TANK Museum, Shanghai; Today Art Museum, Beijing; CyFest, Venice; Edinburgh Futures Institute, UK; Zabludowicz Collection, London; Frankfurter Kunstverein, Germany; Ars Electronica 2017, Austria; Victoria and Albert Museum, London; LABoral Centro, Spain; Nature Morte, Delhi, India, Centre for the Future of Intelligence, UK and more.



 Arts
  H.05 (pav. H) - Jake Elwes
 2021

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Dati aggiornati il 09/11/2021 - 11.51.35