- Year of birth, place
- 1993, London, United Kingdom
- lives and works in
- London, United Kingdom
Jake Elwes (UK), born 1993, is currently based in London. His recent works have looked at Artificial Intelligence, investigating the technology, philosophy and ethics behind it. Jake graduated with a BA in Fine Art from the Slade School of Fine Art (UCL), London in 2017, having also attended SAIC, Chicago (Erasmus), in 2016 and Central St Martins (foundation) in 2012 and is currently currently working with Steve Fletcher at The Artist Development Agency.
Jake has exhibited in the UK and internationally, including Bloomberg New Contemporaries 2017, Newcastle & London, UK; Ars Electronica 2017, Linz, Austria; Victoria and Albert Museum, London, UK; City Loop, Barcelona, Spain; NIPS 2017, Long Beach, US; Nature Morte, Delhi, India; ZKM | Karlsruhe, Germany; Frankfurter Kunstverein, Germany and Centre for the Future of Intelligence (CFI), Cambridge, UK.
Lecture at the Open Conference »Art and Artificial Intelligence«
This talk considers the role played by deep learning algorithms in my artwork. The creative possibilities opened up by machine learning and the implications of generating new original content from an algorithm – which has learnt from vast amounts of data using generative neural networks – seem conceptually extraordinary. Early experiments included generating images of electric sheep, clouds in skies, and tricking a censoring algorithm into producing synthetic pornography. I went on to ask how far I could push an algorithm trained to generate humanly recognizable images into abstracted and unpredictable outcomes (Latent Space 2017), setting off language and image generating models to have conversations (Closed Loop 2017), and taking neural birds back into a natural landscape (Cusp 2019).
This rapidly developing field raises many issues, from old philosophical, political and ethical questions to creative dilemmas. What happens to artistic agency when working with artificial intelligence? What does it mean to collaborate creatively with an unpredictable algorithm, learning from datasets unsupervised, and how does this fit into a history of conceptual and systems art?