ADA – Artificial Digital Aesthetics

Interactive installation / application / technological other

– reflecting on the relationship between artificial intelligence and art

First published in Hyvinkää Art Museum / June 2019

Download ADA to your Android device here:
https://play.google.com/store/apps/details?id=com.brainsonart.ada

ADA is an artificial intelligence who wants to learn about art. Show something beautiful, interesting or surprising to ADA by taking pictures with the application. ADA tells you what it thinks of the picture and you can try to influence ADA’s taste by justifying your own answer with keywords. ADA learns by seeing more art and its artistic taste is constantly evolving. The more ADA sees, the more enlightened reviews it will make. All images taken with ADA develop artificial intelligence that interprets art and aesthetics.

For the user, ADA is essentially an Android application. In the application, ADA prompts you to show it images using the camera on your phone. ADA uses a variety of machine vision and machine learning techniques to form an opinion on a low level (e.g., color of the surface of the surface, boundaries of the color surfaces / contours) and, on the other hand, at a higher level (e.g. identification of objects possibly visible in the picture). ADA tries to describe what features it sees in the picture and what it thinks of it.

Artificial intelligence and machine learning algorithms have gained a foothold as agents producing aesthetic assessments. They influence our everyday aesthetic choices: what music we listen, what images we see online and, more recently, they can also judge photo contests (EyeEm Awards 2018). But how does artificial intelligence learn aesthetics and what is its sensorial world? In the artistic project ADA, we are proposing ways to interpret aesthetics to artificial intelligence and reflect on how the machine could experience art.

The project explores the potential and boundaries of art and aesthetics in the post-human era defined by the growing influence of non-human agents and intelligent systems in all walks of life. It is not self-evident what kind of aesthetics these new systems learn or produce. In the ADA project, the theme is approached from the sensory world of the machine, teaching the machine to see art.

The project is realized by the interdisciplinary Brains on Art collective. Brains on Art draws its theoretical framework from the fields of artistic research, aesthetics, machine learning and cognitive science, and examines the translation of aesthetic experience into an understandable form for a machine. Is it possible for a machine to emulate aesthetic experiences and how to open up the machine’s way of seeing to the public? The project is a suggestion of a machine’s understanding of art and aesthetic experience.

     

 

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