The Creativity Recession and Why Product Leaders Must Reverse It Now

About this episode

Our latest guest is Maya Ackerman — AI‑creativity researcher, professor, and author of Creative Machines: AI, Art & Us (Wiley), as well as founder of WaveAI and LyricStudio (View recent colab with NVidia).

Maya’s perspective is not just insightful — it’s a necessary reality check for anyone building AI today. She challenges the comforting narrative that AI is a neutral tool or a natural evolution of creativity. Instead, she exposes a truth many in tech avoid: AI is being deployed in ways that actively diminish human creativity, and businesses are incentivized to accelerate that trend.

Her research shows how overly aligned, correctness-first models flatten imagination and suppress the divergent thinking that defines human originality. But she also shows what’s possible when AI is designed differently — improvisational systems that spark new directions, expand a creator’s mental palette, and reinforce human authorship rather than absorbing it.

This episode matters because Maya names what the industry refuses to admit. The problem is not “AI getting too powerful,” it’s AI being used to replace instead of elevate. Businesses are applying it as a cost-cutting mechanism, not a creative amplifier. And unless product leaders intervene, the damage to creativity — and to the people who rely on it for their livelihoods — will become irreversible.

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We’re engineering a global creative regression and pretending we aren’t.

Generative AI could radically expand human imagination, but the systems we deploy today overwhelmingly suppress it. The literature is unequivocal:

* AI boosts creative output only when tools are intentionally designed for exploration, not correctness.

* When aligned toward predictability, AI drives conformity and sameness.

* The rise of “AI slop” is not an insult — it’s the logical outcome of misaligned incentives.

* New evidence shows that AI-assisted outputs become more similar as more people use the same tools, reducing collective creativity even when individual outputs look “better.”

* Homogenization is measurable at scale: marketing, design, and written content generated with AI converge toward the same tone and syntax, lowering engagement and cultural diversity.

* Repeated reliance on AI weakens human ori