Perceptron Orchestra by Zoé Aegerter: opening at the Villa Arson
- Innovation
- Research
- Culture
Published on March 5, 2025
–
Updated on March 26, 2025
Dates
from March 7, 2025 to April 7, 2025
Opening on March 6 from 6:00 pm
Location
Campus Villa Arson
The Villa Arson art centre is presenting a solo exhibition by designer Zoé Aegerter, I'm not a cowboy, Daisy - Music for Laboratory.
Produced as part of a residency funded by the 3IA Côte d'Azur and coordinated by the Direction de la Culture of Université Côte d'Azur, Zoé Aegerter's work explores the relationship between language and technology, helping to open up a new creative field for design.
Zoé Aegerter's exhibition brings together three works of incorporation - incorporation of forms, words and relationships - in which the body is restored to its full importance as an instrument of knowledge, proposing an unexpected dialogue with artificial intelligence systems. At the heart of the designer's process is Daisy Bell, a popular song from the late 19th century that has become a sign of a changing era, of a technological mutation whose effects we are only just beginning to measure. Originally known as On a Bicycle Made For Two (Harry Dacre, 1892), it was the first song to be reproduced using voice synthesis (Bell Laboratories, IBM, 1961). A few years later, it appeared in director Stanley Kubrick's 2001, A Space Odyssey, performed by HAL 9000, a character embodying the threat of an artificial intelligence devoid of empathy. In this way, Daisy Bell succeeded in bringing together the festive spirit of the music hall and the undeniably ambivalent spirit of a technology that seems intent on competing with humans.
It is this discreet icon of artificial intelligence that Zoé Aegerter has chosen as the text and sound material for her research. Invited to take up a creative residency at the Institut Interdisciplinaire pour l'Intelligence Artificielle (Université Côte d'Azur), the designer focused on the automatic learning mechanisms of current AI systems. These learning systems are based on two movements: on the one hand, the mathematical interpretation of the functioning of biological neurons: these are artificial neural networks. Secondly, the digital interpretation of the traces of our activities: this is the work of data, the aim of which is to feed these learning networks. Does this mean that these systems resemble us? Can we resist such reductionism? Not to mention their enormous complexity. So, beyond the obstacle of explicability, can we still share a little common sense with these technologies with their anthropomorphic pretensions?
Many members of the Institut staff contributed to the project by lending their voices to Zoé and her team!
Learn more
Zoé Aegerter's exhibition brings together three works of incorporation - incorporation of forms, words and relationships - in which the body is restored to its full importance as an instrument of knowledge, proposing an unexpected dialogue with artificial intelligence systems. At the heart of the designer's process is Daisy Bell, a popular song from the late 19th century that has become a sign of a changing era, of a technological mutation whose effects we are only just beginning to measure. Originally known as On a Bicycle Made For Two (Harry Dacre, 1892), it was the first song to be reproduced using voice synthesis (Bell Laboratories, IBM, 1961). A few years later, it appeared in director Stanley Kubrick's 2001, A Space Odyssey, performed by HAL 9000, a character embodying the threat of an artificial intelligence devoid of empathy. In this way, Daisy Bell succeeded in bringing together the festive spirit of the music hall and the undeniably ambivalent spirit of a technology that seems intent on competing with humans.
It is this discreet icon of artificial intelligence that Zoé Aegerter has chosen as the text and sound material for her research. Invited to take up a creative residency at the Institut Interdisciplinaire pour l'Intelligence Artificielle (Université Côte d'Azur), the designer focused on the automatic learning mechanisms of current AI systems. These learning systems are based on two movements: on the one hand, the mathematical interpretation of the functioning of biological neurons: these are artificial neural networks. Secondly, the digital interpretation of the traces of our activities: this is the work of data, the aim of which is to feed these learning networks. Does this mean that these systems resemble us? Can we resist such reductionism? Not to mention their enormous complexity. So, beyond the obstacle of explicability, can we still share a little common sense with these technologies with their anthropomorphic pretensions?
Many members of the Institut staff contributed to the project by lending their voices to Zoé and her team!
Learn more
