Gabriel Kahan

Gabriel Kahan

Creative Practitioner and Technologist, Berggruen Fellow

Biography

Gabriel Kahan works at the intersection of art, pedagogy, and collective intelligence. For over 10 years he worked closely with local and national governments, NGO’s and schools, creating and deploying online educational content, impacting over 4 Million students and teachers in the US and the Americas. Between 2014-2017 Gabriel was a researcher and lecturer at MIT’s Program in Art, Culture and Technology where he developed a collaborative learning method to help diverse groups of people from varied backgrounds and abilities identify, understand and express common yet complex situations, through deep thinking, design management and manufacturing, and artistic reification. As a Berggruen Fellow, Gabriel is deploying the method throughout Los Angeles to create an urban collective-intelligence resource to help people from all backgrounds and abilities, have a civic voice in their community, understand their city and their place within it, guide multi-pronged decision making, and create new perspectives, together.


composed by Arswain
machine learning consultation by Anna Tskhovrebov
commissioned by the Berggruen Institute
premiered at the Bradbury Building
downtown Los Angeles
april 22, 2022

Human perception of what sounds “beautiful” is necessarily biased and exclusive. If we are to truly expand our hearing apparatus, and thus our notion of beauty, we must not only shed preconceived sonic associations but also invite creative participation from beings non-human and non-living. We must also begin to cede creative control away from ourselves and toward such beings by encouraging them to exercise their own standards of beauty and collaborate with each other.

Movement I: Alarm Call
‘Alarm Call’ is a long-form composition and sound collage that juxtaposes, combines, and manipulates alarm calls from various human, non-human, and non-living beings. Evolutionary biologists understand the alarm call to be an altruistic behavior between species, who, by warning others of danger, place themselves by instinct in a broader system of belonging. The piece poses the question: how might we hear better to broaden and enhance our sense of belonging in the universe? Might we behave more altruistically if we better heed the calls of – and call out to – non-human beings?

Using granular synthesis, biofeedback, and algorithmic modulation, I fold the human alarm call – the siren – into non-human alarm calls, generating novel “inter-being” sonic collaborations with increasing sophistication and complexity. 

Movement II: A.I.-Truism
A synthesizer piece co-written with an AI in the style of Vangelis’s Blade Runner score, to pay homage to the space of the Bradbury Building.

Movement III: Alarmism
A machine learning model “learns” A.I.Truism and recreates Alarm Call, generating an original fusion of the two.

Movement IV: A.I. Call
A machine learning model “learns” Alarm Call and recreates A.I.Truism, generating an original fusion of the two.


RAVE (IRCAM 2021) https://github.com/acids-ircam/RAVE