LOOKING FOR LOVE
Fast Familiar (2023)
Can you teach a robot how to love?
Part modern-day tamagotchi, part interactive fiction, Looking for Love is a playful experience that takes place over a message-based dating app.
Take a seat in Fast Familiar’s ‘internet cafe’ to teach a robot about romance. Surely training the machine on everything the internet knows about love will result in unparalleled romantic success? In your role as a wing-(hu)man, you’ll provide advice, encouragement and be that vital shoulder to cry on when things don’t work out…
Help the machine distil the essence of romance from movies, poems and song lyrics; compare your definitions of love; and determine how much of a role you want data to play in your own love life.
Blending artificial Intelligence, human intuition and everything that gets lost in translation, this artwork invites you to take the perspective of another form of intelligence, to reflect on the peculiarities of our own.
CREDITS
Originally presented by Science Gallery London
Fast Familiar: Rachel Briscoe, Joe McAlister, Dan Barnard
User interface design: Diana Monova
Associate computational artist: Owen Planchart
Supported using public funding by the National Lottery through Arts Council England
FAST FAMILIAR create audience-centric projects that are part art and part social experiment. They are a longterm interdisciplinary collaboration comprising expertise in narrative design, facilitation and creative computing. Their work is participatory, playful and political. For Fast Familiar, art is a space to explore questions which are too complex for daily life, and where we can collectively imagine and rehearse different ways of being. They are fascinated by how digital technology can enable new forms of human connection in a rapidly changing world, and they believe in polyphonic experiences, complexity and the power of humour. Their award-winning projects can be found in museums, galleries, theatres, parks, town centres and on the internet. Website / Instagram / Twitter