Dan Taber, PhD
AI & Institutional Change
Most AI strategy focuses on tools and deployment. The biggest failures show up later — in the people, incentives, and organizational systems that determine whether AI creates value or chaos.
I’ve worked for more than a decade at the intersection of AI, safety, and institutional change, building and advising programs at scale at Spotify and Indeed and developing practical frameworks through the Berkman Klein Center at Harvard. Across these settings, I’ve seen the same pattern repeat: organizations invest heavily in AI capabilities while underinvesting in how decisions get made, organizational design, and governance.
About Me
My path hasn’t been linear. I started in academia, earned a PhD in Epidemiology, worked on federal nutrition policy, and eventually moved into technology, where I’ve led Trust & Safety and Responsible AI work serving hundreds of millions of users.
The common thread has been an interest in how change actually happens — and why it often doesn't. Organizations adopt AI readily; transforming how they work is a different problem entirely. I'm less interested in AI's capabilities than in the organizational systems that determine whether it creates value.
What I Focus On
I focus on the organizational patterns that emerge when AI adoption outpaces institutional strategy. These typically revolve around incentives, accountability, and organizational design.
AI hype that's outpacing the organization's ability to make sense of it
Governance that exists on paper but breaks down under real incentives
AI initiatives that stall because no one owns the transformation