Dan Taber, PhD
AI, Institutions, & Workforce Transformation
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 workforce readiness, how decisions get made, 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.
That path taught me that the hardest problems aren’t technical. They’re organizational. I’m less interested in what AI can do than in what happens to the people and institutions trying to use it well.
What I Focus On
I focus on the organizational failure modes that emerge when AI moves faster than the people and institutions using it. These typically revolve around incentives, accountability, and workforce readiness.
AI enthusiasm that outpaces workforce readiness and role clarity
Governance that exists on paper but breaks down under real incentives
AI initiatives that stall because accountability is diffuse or unclear