Musicians Coding AI for Themselves

Regular price €49.99
Title
Quantity:
Will Deliver When Available
Will Deliver When Available
14 days return policy Shipping & Delivery
AI art
AI ethics
AI music
algorithmic composition
Category=AVA
Category=AVLA
Category=AVLP
Category=AVP
Category=KNTF
Category=UYQ
Category=UYU
co-creative systems
composer-performer
eq_art-fashion-photography
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_music
eq_nobargain
eq_non-fiction
forthcoming
intermedia
Machine learning
music technology
neural networks
performing arts

Product details

  • ISBN 9781041016663
  • Dimensions: 156 x 234mm
  • Publication Date: 01 Sep 2026
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
Secure checkout Fast Shipping Easy returns

Musicians Coding AI for Themselves blends cutting edge academic research with the real-world experiences of musicians working the intersection of music and AI. This book not only reflects on the philosophical implications of AI in music but also offers readers insights into the technical inner workings of bespoke, artist-crafted AI systems.

The chapters are written by emerging and innovative coder-musicians who present their own artistic practice and research, with a focus on creative, ethical, collaborative, and educational uses of AI. Interviews with leading musicians who have incorporated AI into their work traverse diverse topics, from behind-the-scenes details of how each artist uses AI in their music to the greater conceptual impact of AI on the arts, the future of music technology, and the creative process.

This book will be of interest to practicing musicians who wish to harness the creative potential of AI in their music and understand its implications for the industry on a wider scale. It will also be of interest to students of music composition, music studies, experimental music, music technology and human-computer interaction.

Constantin Basica, DMA, is a Romanian composer whose work focuses on symbiotic interrelations between music, video, and performers. His music has been presented internationally by distinguished artists at events such as MATA Festival, Ars Electronica Festival (Bucharest Garden), World New Music Days, George Enescu Festival, and the International Computer Music Conference. He earned his doctorate in composition and completed postdoctoral training at Stanford University. In recent years, he has collaborated with researchers on developing AI tools for co-creativity that explore “translations” between media. Basica is a lecturer in music at Stanford’s Center for Computer Research in Music and Acoustics (CCRMA).

Julie Zhu, DMA, is a composer, artist, and carillonist. Her work stands interstitial to instrumental music, electronics, and performance within settings ranging from chamber music stagings to museum sound installations to experimental film scores. Concision and poetry characterize her music, with commissions from Radio France, Dark Music Days Reykjavík, GMEM Marseille, GRAME Lyon, and Chamber Music America. Her research on music and AI focuses on the project Deep Drawing, which tests a machine’s ability to bring the intricate noises of drawing and writing to visual life. Zhu is an assistant professor of performing arts technology at the University of Michigan.