On this week’s podcast episode, I talk with Jonathan Wyner, mastering engineer at M-Works, Berklee professor, head of artistic technology initiatives for BEATL, and past president of the Audio Engineering Society . . .
. . . about what AI can do in mastering, mixing, education, and music creation, and where the human element still matters most.
Jonathan breaks down why AI mastering has not affected his own client work in a meaningful way, why he once tried to replace himself with AI, how generative AI can help with idea generation but still struggles with control and quality, and why mentorship, taste, and human judgment remain central to great records.
We also dig into Berklee’s AI music summit, copyright questions around AI-generated tracks, and the bigger creative and business shifts happening across the music industry.
In This Episode:
- Why Jonathan says AI mastering still cannot match the human listening pass
- What happened when he tried to replace his own mastering work with AI
- Why AI mastering may be cheap, but still misses intention, judgment, and taste
- Why AI mixing is a far harder problem than most people think
- How AI is changing music education, evaluation, and mentorship
- What Berklee’s AI music summit is trying to solve for artists and creators
- Where generative AI helps music creation, and where it breaks down fast
- Why copyright, ownership, and future workflows are still wide open questions
And much more.
You can hear it at bobbyoinnercircle.com, or via Apple Podcasts, Amazon Music, YouTube Music, Mixcloud, Spotify, Deezer, TuneIn Radio, or RadioPublic.
Also, a video version of this podcast is now available on YouTube as well.
