Niall Ferguson

Niall Ferguson

Senior Fellow at the Hoover Institution, Stanford University

Biography

Niall Ferguson is the Laurence A. Tisch Professor of History at Harvard University and William Ziegler Professor of Business Administration at Harvard Business School. He is also a Senior Research Fellow at Jesus College, Oxford University, and a Senior Fellow at the Hoover Institution, Stanford University.Born in Glasgow in 1964, he was a Demy at Magdalen College and graduated with First Class Honours in 1985. After two years as a Hanseatic Scholar in Hamburg and Berlin, he took up a Research Fellowship at Christ’s College, Cambridge, in 1989, subsequently moving to a Lectureship at Peterhouse. He returned to Oxford in 1992 to become Fellow and Tutor in Modern History at Jesus College, a post he held until 2000, when he was appointed Professor of Political and Financial History at Oxford. Two years later he left for the United States to take up the Herzog Chair in Financial History at the Stern Business School, New York University, before moving to Harvard in 2004.

His publishing career is an award-winning list historical volumes several of which have been best sellers. These Paper and Iron: Hamburg Business and German Politics in the Era of Inflation 1897-1927 (Cambridge University Press, 1995), Virtual History: Alternatives and Counterfactuals (Macmillan, 1997); The Pity of War: Explaining World War One (Basic Books) and The World’s Banker: The History of the House of Rothschild (Penguin); The Cash Nexus: Money and Power in the Modern World, 1700-2000 (Basic).

Niall is a prolific commentator on contemporary politics and economics and a regular contributor to television and radio on both sides of the Atlantic. He wrote and presented a six-part history of the British Empire for Channel 4, as well as a PBS series Twentieth Century Conflict and the Descent of the West. He writes and reviews regularly for the British and American press. He is a contributing editor for the Financial Times and a regular contributor to Newsweek. In 2004 Time magazine named him as one of the world’s hundred most influential people.

Ferguson was previously a member of the Council for the Future of Europe and The WorldPost Advisory Council.


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