Fair, Explainable, and Lawful Machine Learning for High-Stakes Applications

Fair, Explainable, and Lawful Machine Learning for High-Stakes Applications

Explore the critical aspects of fair, explainable, and lawful machine learning for high-stakes applications in this 35-minute talk by Sanghamitra Dutta from the University of Maryland, College Park. Delve into information-theoretic methods for trustworthy machine learning, focusing on their application in sensitive and consequential scenarios. Gain insights into the challenges and solutions for developing AI systems that are not only accurate but also ethical, transparent, and compliant with legal standards. Learn how these principles can be applied to ensure responsible AI deployment in fields such as healthcare, finance, and criminal justice.