An Evening with Holly Herndon and Mat Dryhurst

DESCRIPTION:

In an age of AI crossing over into art and beyond, how do artists navigate ethics, ownership, and creativity? Berlin-based artists Holly Herndon and Mathew Dryhurst may have an answer. Together, they create precedent-setting projects where technical systems are artworks unto themselves—work they describe as “Protocol Art,” interventions at the level of systems and protocols rather than objects, arguing for agency at the infrastructure layer. This idea creates art that doesn't just use today's technologies but also pulls back the curtain on them.

What to Expect:

Herndon and Dryhurst will present aspects of their pioneering work at the intersection of music, visual art, ethics, technology, infrastructure, and governance. The evening will include a discussion and audience Q&A facilitated by USC Vice Provost for the Arts and Annenberg professor Josh Kun, examining the questions that shape their artistic practice and the general skepticism around the future of generative AI and the arts.

Bios:

Holly Herndon holds a doctorate in Computer Music from Stanford University. Her awards include the 2022 Ars Electronica STARTS prize, Austria's first Digital Human Rights Award (2024), the Kairos Prize (2025), and the Deutschen KI Prize (2025).

Mathew Dryhurst is a Senior Research Associate at HAI Lab and fellow at the Institute for Ethics in AI at Oxford University, and has held faculty positions at NYU and the European Graduate School. He is a widely consulted voice on AI policy, copyright, and the political economy of cultural production, contributing to debates around data rights and the governance of generative AI.

Herndon and Dryhurst run Herndon Dryhurst Studio and have co-produced critically acclaimed albums Platform (4AD/RVNG 2015) and PROTO (4AD/2019), and developed Holly+, a protocol for shared ownership and licensing of an artist's identity and intellectual property. In 2022, they co-founded Spawning, an organization that attempted to build a web-scale data permissions protocol for AI. Its tools Have I Been Trained and the Do Not Train standard—covering 2 billion+ works—proved influential in machine learning policy discussion.