Public Knowledge: Face2Face | Lee Gamble
Hello Humans — By way of introduction, this is an essay about mimicry, fraud, lies, the future, reality, confusion, entities, mirrors, reflections, deepfakes, trust and information. It’s about a strange new landscape of synthetic-human lyrebirds.
Face2Face is created in the style of a ‘film essay’. It is constructed from truths, half-truths, artificially generated emotion, lies, A.I music, doppelgängers, AI-generated news feeds, mimicry and deepfakes. A social-hyper-realism that surveys the digital entities set to further transform and confuse. Objective facts are knowledge, and knowledge is a function of the human’s ability to trust information — but here there can be no real trust, because there is no real information.
In the deepfake, knowledge is hollowed-out anew as it evolves and develops into a divergent hallucination of ourselves and trust disintegrates into pure daemonized content.
“Well, what you have here is the human input and then the hallucinations. Things are reacting to these inputs, creating a sense of image, creating a sense of reality – out of which a story might seem to appear.”
Lee Gamble is an artist, electronic music composer, label owner and DJ of exploratory electronic/dance music. Over the last several years Lee has released a string of critically acclaimed albums and EP’s on seminal electronic music labels PAN and Hyperdub, he also minted his own UIQ imprint in late 2015.
Gamble’s audio-visual live shows, music and work incorporate recurring themes of hallucination, futurology, nostalgia and memory, reality and the imaginary, social realism, the sound objects of musique concrète and the ever mutating dancefloor mechanics of the hardcore continuum.
In 2017 Gamble worked alongside the London Contemporary Orchestra composing two acoustic pieces which explored the ‘archaeoacoustics’ of the Great Masson Cave where they were premiered and created. His writing was recently published in the book Audint—Unsound: Undead (Urbanomic).
Image Credit: Non-Humans imagined by a GAN (generative adversarial network). Collaged by Lee Gamble