The Governance of Responsible Machine Learning for Consumer Audience Modeling
Artificial Intelligence is rapidly transforming Direct-To-Consumer healthcare advertising, but with that evolution comes a pressing challenge: how to responsibly unlock insights from sensitive health data without compromising privacy, transparency, or control. Traditional safeguards are being stretched thin as AI uncovers subtle patterns that can be misused, making it essential to rethink how data is protected and modeled in high-risk domains like healthcare.
This whitepaper introduces synthetic trends, a breakthrough approach to machine learning that converts raw health data into secure, abstract representations. These trends preserve predictive power while dramatically reducing privacy risks, enabling scalable modeling across federated environments. Download the whitepaper to explore how synthetic trends offer a resilient, privacy-first foundation for responsible AI in healthcare.
