Philip Grant

Philip Grant

ToftH Researcher

Biography

Philip Grant is a Los Angeles-based researcher at Transformations of the Human, investigating how artificial intelligence and machine learning deployed in financial markets might challenge long-established notions of human intuition, judgment, and experience. He is an anthropologist and historian who was previously Research Fellow in the Social Studies of Finance at the University of Edinburgh, where he drew on both field research and his own earlier career as an equity fund manager to write a co-authored book on investment management entitled Chains of Finance (OUP). As part of that project, he worked with artists Goldin+Senneby, publishing an account of this collaboration in e-flux. He has also been a Persian-English translator and editor of academic works on Middle Eastern history, and is convinced that any enquiry into the human must operate in constant translation between as many languages as possible. He studied at Oxford, Sciences-Po Paris, and the University of California Irvine, where his PhD research was based on collaborative fieldwork with Iranian-American feminist activists.


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