Jake Elwes

Jake Elwes is a British media artist. He was a 2021 finalist for the Lumen Prize.[1] His practice is the exploration of artificial intelligence (AI), queer theory and technical biases.[2] He is known for using AI to create art in mediums such as video, performance and installation.[3] His work on queering technology addresses issues caused by the normative biases of artificial intelligence.[4][2]

Education and early life

Jake Elwes studied at the Slade School of Fine Art where he began using computer code as a medium.[3]

In 2016 he attended the School of Machines, Making & Make-Believe in Berlin with artist and educator Gene Kogan.[3]

He was introduced to drag performance by his boyfriend who holds a Phd in drag performance which is instrumental to his work.[2]

Career

Elwes work with artificial intelligence is cited as a hopeful strategy to make AI more playful and diverse.[5] He has exhibited in museums and galleries in Europe and the Asia including Gazelli Art House[6] and Arebyte gallery.[2][7]

Installations projecting conversations between two neural networks

Elwes has created works based on the conversations between two neural networks including Closed Loop, 2017 and 2016's Auto-Encoded Buddha which was a tribute to Nam June Paik's TV Buddha (1974). In Auto-Encoded Buddhawhich a computer struggles with the notion of Buddha's philosophy.[3]

Zizi & Me

Zizi & Me is a deep fake drag act based on artificial intelligence (AI). It has been presented live and as interactive online artwork. It is an exploration of queer culture and the algorithms philosophy and ethics of AI.[8] The work questions if AI can be used to explore and celebrate queer identities. The avatars within Zizi are deepfakes that playfully exaggerates the human form. They are generated by a hacked artificial intelligence (AI) system. They were made to challenge the biases that have been built into many of the most commonly used facial recognition technologies.[2]

Knowing that facial recognition technology statically struggle to recognize black women or transgender people, Elwes set out to "Queer the Dataset" through the open-sourced generative adversarial network (GAN). Jake added a dataset of 1,000 photos of drag kings and queens into GAN's 70,000 faces collected in a dataset called Flickr-Faces-HQ Dataset (FFHQ). He then crated new simulacra faces, known as deep fakes.[2]

References
  1. "Inside A.I. Art". The Lumen Prize. Retrieved 31 October 2021.
  2. "Meet the artist queering AI technology". The Independent. 30 July 2021. Retrieved 26 September 2021.
  3. "Episode I. Artificial Intelligence and Drag Performance: Jake Elwes's "The Zizi Project" |". Flash Art. 23 October 2020. Retrieved 27 September 2021.
  4. Condliffe, Jamie (15 November 2019). "The Week in Tech: Algorithmic Bias Is Bad. Uncovering It Is Good". The New York Times. ISSN 0362-4331. Retrieved 31 October 2021.
  5. Gleadell, Colin (19 February 2019). "Can AI be a big hitter in the art world? Sotheby's first AI work at auction could sell for £40,000". The Telegraph. ISSN 0307-1235. Retrieved 27 September 2021.
  6. "Zizi - Queering the Dataset | Artsy". www.artsy.net. Retrieved 27 September 2021.
  7. "Cede Control of Your Web Browser to This High Tech Exhibition". ocula.com. 27 September 2021. Retrieved 27 September 2021.
  8. Wade, Mike. "'Deep fake' drag act is the new reality". ISSN 0140-0460. Retrieved 26 September 2021.
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