About Me

I work on how organizations make consequential decisions about AI. How they evaluate emerging systems, what evidence they trust, and how they navigate uncertainty when established playbooks don’t yet exist.

My career has been a series of pivots that only make sense in retrospect. I started as a humanities major, earned a PhD in Epidemiology, spent years in academic research that influenced federal nutrition policy, then moved into technology — first at Indeed, where I founded the company’s Responsible AI function, and now at Spotify, where I lead Research and Applied AI in Trust & Safety.

The thread connecting those experiences isn’t AI or even technology. It’s a fascination with what happens when technical systems meet organizational reality. I’m drawn to problems where the answer isn’t simply better algorithms or better policy, but better ways of evaluating evidence, understanding risk, and making decisions under uncertainty.

As a Fellow at Harvard’s Berkman Klein Center, I co-created AI Blindspot, a framework that helps organizations identify structural blind spots in AI systems. Whether in public health, technology, or Trust & Safety, I’ve found myself returning to the same question: how can organizations make better decisions when the stakes are high and the answers aren’t obvious?