1ch HD Video, made with custom software using AI Deep Learning, duration: 3:02, 2017
An artificial neural network making predictions on live webcam input, trying to make sense of what it sees, in context of what it’s seen before. It can see only what it already knows, just like us.
‘Learning To See’ is an ongoing series of works that use state-of-the-art Machine Learning algorithms as a means of reflecting on ourselves and how we make sense of the world. The picture we see in our conscious minds is not a direct representation of the outside world, or of what our senses deliver, but is of a simulated world, reconstructed based on our expectations and prior beliefs.
The work is part of a broader line of inquiry about self affirming cognitive biases, our inability to see the world from others’ point of view, and the resulting social polarisation.
Memo Akten is a computational artist from Istanbul, Turkey working primarily in moving image, light and sound; producing work spanning disciplines such as video, installation, performance, online works and dance.
His work explores the collisions between nature, science, technology, ethics, ritual, tradition and religion. He studies and works with complex systems, behaviour and algorithms, and combining critical and conceptual approaches with investigations into form, movement and sound he creates data dramatizations of natural and anthropogenic processes.
Alongside his practice, he is currently working towards a PhD at Goldsmiths University of London in artificial intelligence and expressive human-machine interaction, exploring collaborative co-creativity between humans and machines.
Akten received the Prix Ars Electronica Golden Nica in 2013 for his collaboration with Quayola, ‘Forms’. Exhibitions and performances include the Grand Palais, Paris; Victoria & Albert Museum, London; Royal Opera House, London; Garage Center for Contemporary Culture, Moscow; Holon Design Museum, Israel and the EYE Film Institute, Amsterdam.