Andrew Scheps says AI tech will ‘take your job’ in production only if you let it
“Because by definition machine learning can’t create new stuff. It’s amalgamating a gigantic amount of existing stuff.”
Image: ICMP – Institute of Contemporary Music Performance via YouTube
Andrew Scheps, Grammy Award-winning mixing engineer and former Red Hot Chili Peppers collaborator, has offered his thoughts on the rise of AI technology in the production realm.
In a recent chat with London’s Institute of Contemporary Music Performance, Scheps touched on the pros and cons of machine learning technology, addressing in particular concerns that AI tools might someday replace jobs in production.
“It’s always going to be very biased towards the data it’s trained on,” Scheps began “So I think that the technology and some of the software that’s been written is amazing — all the iZotope stuff… it’s really incredible but if you try to extend it to things like songwriting… although there’s some K-Pop stuff happening in that realm already.”
“But any of the more creative side of it [with] mixing, mastering — there are plenty of online mastering places now that are all based on algorithms but what they’re based on is someone saying, ‘This is what good songs sound like when they’re mastered’.”
“But what always moved things forward is the thing like nothing you’ve ever heard before,” Scheps emphasised, citing Beck Odelay and AC/DC’s Back In Black as examples of works that “scared people”, because “it was new and that was what was great, and you’ll never get that with machine learning.”
“It’s impossible — it goes against what machine learning is,” he added. “So I think some of the tools are really, really incredible but I think if you let them just do their thing then the reality of, ‘that thing can take your job’ is true because then you just let it.”
Nevertheless, Scheps maintains that proper use of machine learning technology can be very helpful in teaching tomorrow’s mixers.
“Where I think it’s really helpful, especially for young people, is to use something like [iZoptope] Ozone — let it listen to your track, suggest a bunch of stuff and then rip that apart. See what it’s doing, every little thing, and try reordering stuff. See what you like and what you don’t like and train yourself to do what it did,” Scheps explained.
“And it’s an amazing teaching tool, but in terms of throwing a bunch of notes at a computer and having it make a record for you, I would argue it’s just going to be a bunch of boring records.”
“Because by definition machine learning can’t create new stuff. It’s amalgamating a gigantic amount of existing stuff.”
