At TEDNext in Atlanta, producer Poo Bear—the person behind Justin Bieber's "Yummy"—did something that would have seemed absurd five years ago: he had a live songwriting duel with an AI.
The opponent was Suno, an AI platform trained to generate music. The stakes were simple: prove whether machines could do what humans do in the studio.
Poo Bear went first. He crafted a pop hook on the spot about "starting over," singing it with the kind of vulnerability that comes from actually understanding what the words mean. Then he fed the same prompt to Suno and let it work.
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Start Your News DetoxWhat came back was technically competent—the AI had learned rhythm, melody, structure. But it was also scattered. The lyrics didn't cohere. There was no emotional through-line, no sense that someone had felt what they were singing. As Poo Bear put it simply: "It didn't really make a lot of sense, but it's okay."
The audience voted with their applause. They chose Poo Bear overwhelmingly.
One attendee, Tracy Egbas, articulated what the room felt: "He understood what he was singing and why." That understanding—the intentionality behind every syllable—is the gap that still separates human creativity from algorithmic generation.
This matters because the conversation around AI in creative fields has bifurcated into two camps: either AI will replace artists, or it's worthless. Poo Bear's demonstration suggests a third path. AI tools are getting genuinely useful. They can generate starting points, iterate on ideas, handle technical grunt work. But they can't yet do what humans do instinctively: embed meaning into art.
The producer's conclusion was pragmatic rather than defensive: "We are still always going to need humans." Not because humans are inherently superior, but because art that resonates requires intention. It requires someone on the other side of the performance who cares about what the song is saying.
The real story here isn't that AI lost a songwriting battle. It's that the creative industries are learning to ask better questions. Not "Can machines replace us?" but "What can machines handle so we can focus on what only we can do?" That shift—from fear to integration—is where the actual evolution happens.
