Governance as Proof of Trust — with Dr. Kate Eisenberg, Dyna AI Artwork

Wonder Lab

Wonder Lab explores what it takes to build the future inside systems that resist change.

Hosted by Christine Galligan — a strategic innovation leader, researcher, and former caregiver — the show examines why brilliant innovations in healthcare, fintech, education, and climate tech often fail to scale.

Not because the technology doesn’t work, but because the systems weren’t built for change.

Each episode investigates the real jobs to be done of innovation — how ideas earn trust, how systems adapt, and how we balance what’s possible with what’s responsible.

Through expert conversations, research vignettes, and philosophical field notes, Wonder Lab uncovers the human decisions that determine whether innovation becomes transformation… or just another pilot that stalls.

For: builders, governance leaders, and strategists working where innovation meets human dignity.

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Governance as Proof of Trust — with Dr. Kate Eisenberg, Dyna AI

November 04, 2025 • Christine Galligan • Season 1 • Episode 1

“If you’re using one of these tools, you’re effectively overseeing it.”
— Dr. Kate Eisenberg, Dyna AI

Every week, another AI tool promises to transform healthcare. But the real question isn't can we build it — it's should we deploy it? And who gets to decide?

Dr. Kate Eisenberg is a physician executive leading AI governance at Dyna AI, which means she's the person translating "first, do no harm" into decisions about algorithms evolving faster than evidence can keep up.

In this conversation, we explore:

Where governance shifted from optional to essential
Why there's no single standard for evaluating AI tools (and what that means for builders and health systems)
What happens when AI disagrees with clinical intuition
The difference between human error and model error — and which one we trust more
How interoperability challenges are amplified (not solved) by AI
Kate's call to action: get involved now, while decisions are still being made

This isn't about whether AI belongs in healthcare. It's about who's drawing the lines, how they're drawing them, and whether those lines will hold.

Ways to work with Christine:
https://substack.com/@cgalligan