federated learning

Tim Hwang describes how his Google public policy role connects AI research with governments, regulators, and social impacts. The talk explores fairness and privacy, adversarial vulnerabilities, automation, and the challenge of making machine learning understandable and useful in products. Hwang discusses opportunities in creative tools, small niche applications, cloud machine learning, and on-device learning, while emphasizing that good interfaces and domain knowledge matter alongside research. He closes with recommendations for learning about machine learning and its history, including past cycles of AI hype.