HD Video made with custom software using Artificial Intelligence / Machine Learning / Deep Learning / Generative Adversarial Networks.
Originally made in 2017, minted in Feb 2024.

An artificial neural network looks out onto the world, and tries to make sense of what it is seeing. But it can only see through the filter of what it already knows.

Just like us.

Because we too, see things not as they are, but as we are.

Learning to See is an ongoing collection of works that use state-of-the-art machine learning algorithms to reflect on ourselves and how we make sense of the world. The picture we see in our conscious mind is not a mirror image of the outside world, but is a reconstruction based on our expectations and prior beliefs.

In this context, the term "seeing", refers to both the low level perceptual and phenomenological experience of vision, as well as the higher level cognitive act of making meaning, and constructing what we consider to be truth. Our self affirming cognitive biases and prejudices define what we see, and how we interact with each other as a result, fuelling our inability to see the world from each others' point of view, driving social and political polarization. The interesting question isn't only "when you and I look at the same image, do we see the same colors and shapes", but also "when you and I read the same article, do we see the same story and perspectives?".

This work - and related adaptations such as a realtime live interactive version - has been shown internationally at exhibitions and venues such as the "More human than human" show at the Barbican, London UK; "Cybernetic Consciousness" at Itaú Cultural, Sao Paulo Brazil; Ars Electronica Center, Linz Austria; Haus der Kunst, Munich Germany; Tretyakov Gallery, Moscow Russia; Kate Vass Gallery, Zurich Switzerland; The Wellcome Collection, London UK; Onassis Stegi, Athens Greece; and many others. It has been featured in numerous books and articles on "AI and Art", is included in MIT's Open Documentary Lab, and it was shown during NVIDIA Founder and CEO Jensen Huang's 2019 keynote at GTC (GPU Technology Conference) with the voice-over "[AI is] inventing new ways to bring out the creative genius in us all".

More information about the work can be found in my paper published at SIGGraph 2019
Akten, Memo, Rebecca Fiebrink, and Mick Grierson. "Learning to see: you are what you see." ACM SIGGRAPH 2019 Art Gallery. 2019. 1-6.
https://dl.acm.org/doi/10.1145/3306211.3320143

Extensive information can be found in Chapter 5 of my PhD thesis:
"Deep Visual Instruments: Realtime Continuous, Meaningful Human Control over Deep Neural Networks for creative expression"
https://doi.org/10.25602/GOLD.00030191