Clarence Lee is a digital marketing and data science expert who has taught at Cornell University and is currently launching an AI startup Eisengard.ai. In this episode of the Business Schooled podcast, Lee walks us through a groundbreaking idea: that technologies like deepfakes (often maligned in media) can be repurposed for good. He explains how generative adversarial networks (GANs) can create synthetic versions of real data—notably customer behavior data—to enable privacy-preserving personalization. The twist? These models can work just as well without using actual personal data.
This breakthrough paves the way for a future where consumers own and potentially profit from their data. Clarence uses the analogy of renting versus owning a home: right now, we’re all just tenants in massive data complexes owned by big tech. But what if we had deeds to our own data properties? What if we could rent out anonymized versions and participate in the value we help create?
Clarence’s startup is built around that idea. Think Canva, but for AI: a no-code platform that allows everyday people and small businesses to use dashboards, machine learning models, and generative AI tools without a PhD in computer science. His mission is simple but ambitious—to give non-experts the same data science superpowers that have long been the domain of elite institutions and well-funded tech firms.
And it’s already working. One early user, a climate justice advocate in South Carolina, used Clarence’s tools to measure the effects of environmental harm on his community and make the case for change.
Lee’s core belief? That AI doesn’t just have to make businesses smarter—it can make society fairer. And by rethinking who owns and controls data, we might just give the future a fighting chance to work for everyone.