March 2023
CITP Lecture: Michael P. Kim – Foundations of Responsible Machine Learning
Algorithms make predictions about people constantly. The spread of such prediction systems has raised concerns that machine learning algorithms may exhibit problematic behavior, especially against individuals from marginalized groups. This talk will provide an ...
CITP Distinguished Lecture Series: Lorrie Cranor – Designing Usable and Useful Privacy Choice Interfaces
Users who wish to exercise privacy rights or make privacy choices must often rely on website or app user interfaces. However, too often, these user interfaces suffer from usability deficiencies ranging from being difficult to find, hard to understand, or ...
April 2023
CITP Lecture: Lydia Liu -Towards Responsible Machine Learning in Societal Systems
Machine learning systems are deployed in consequential domains such as education, employment, and credit, where decisions have profound effects on socioeconomic opportunity and life outcomes. High stakes decision settings present new statistical, ...
CITP Lecture: Amanda Coston – Responsible Machine Learning through the Lens of Causal Inference
Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has illuminated numerous examples where these algorithms proved unreliable ...
CITP Lecture: Peter Henderson – Aligning Machine Learning, Law, and Policy for Responsible Real-World Deployments
Machine learning (ML) is being deployed to a vast array of real-world applications with profound impacts on society. ML can have positive impacts, such as aiding in the discovery of new cures for diseases and improving government transparency and efficiency. But it can also be harmful: reinforcing authoritarian regimes, scaling ...