The Art in Artificial Intelligence w/ Daniel Rowland

In 2019, recording artist Grimes made a bold prediction. On Sean Carroll’s Mindscape podcast she was quoted as saying ‘we are nearing the end of art, human art. Once we have actual AGIs (Artificial General Intelligence) they’re going to be so much better at making art than us.’

This assertion highlights one extreme of a polarising debate around the question of AI involvement in the creative arts. With so many blue-collar jobs already upended across various industries, the idea that something as intuitive, subjective and deeply personal as music could be optimised by AI is enough to cause alarm.

But many musicians and artists see the onset of AI as a golden opportunity to push human creativity beyond its current limitations in exciting and unexpected ways. Many individual artists and companies are developing tools that leverage machine learning to augment the creative process, in some ways by automating the more laborious, technical aspects of production allowing humans more time to focus on the creative process itself.

One such company is LANDR, which have been offering AI-assisted mastering since 2014. Despite initial reluctance, LANDR has achieved growing popularity among music industry professionals and, famously, Gwen Stefani’s 2016 release “Make Me Like You” was mastered through the online service.

Our guest today is LANDR’s Head of Strategic Partnerships and Professor of Recording Industry at MTSU in Nashville, Daniel Rowland. Alongside his fascination with the intersection of art and technology, Daniel has also produced the music for an Oscar-winning Pixar film, mastered multi-platinum and Grammy-nominated albums and collaborated on projects with the likes of NIN, Philip Glass, Seal, Gwen Stefani and countless others.

As a firm believer in technologies ability to empower creatives and make the process of producing and releasing music more accessible, Daniel has a deep insight into what music production will look like for the next generation of creators.

Masterclass Details

Event Details


Monday 07 March 2022




Student ID Required.
This event is open to current ACM students, alumni and those enrolled for a course but yet to commence studies.
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