Andrew Trask
Andrew Trask worked on OpenMined, a project for training machine learning models on private user data. The approach combines homomorphic encryption and multiparty computation so that organizations can learn from sensitive data without collecting it in readable form. Trask’s work addresses the tension between useful AI training, user privacy and the concentration of data in large companies.