🔬 Research Summary by Corinna Hertweck, a fourth-year PhD student at the University of Zurich and the Zurich University of Applied Sciences where she is working on algorithmic fairness. [Original paper by … [Read more...] about People are not coins: Morally distinct types of predictions necessitate different fairness constraints
Research Summaries
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
🔬 Research Summary by Shangbin Feng, Chan Young Park, and Yulia Tsvetkov. Shangbin Feng is a Ph.D. student at University of Washington.Chan Young Park is a Ph.D. student at Carnegie Mellon University, studying … [Read more...] about From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
🔬 Research Summary by Stephen Casper, an MIT PhD student working on AI interpretability, diagnostics, and safety. [Original paper by Stephen Casper,* Xander Davies,* Claudia Shi, Thomas Krendl Gilbert, Jérémy … [Read more...] about Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
A Critical Analysis of the What3Words Geocoding Algorithm
🔬 Research Summary by Rudy Arthur, a Senior Lecturer in Data Science at the University of Exeter. [Original paper by Rudy Arthur] Overview: What3Words (W3W) is a geocoding app that has been aggressively … [Read more...] about A Critical Analysis of the What3Words Geocoding Algorithm
Confidence-Building Measures for Artificial Intelligence
🔬 Research Summary by Andrew W. Reddie, Sarah Shoker, and Leah Walker. Andrew W. Reddie is an Associate Research Professor at the University of California, Berkeley’s Goldman School of Public Policy, and Founder … [Read more...] about Confidence-Building Measures for Artificial Intelligence