🔬 Research Summary by Prakhar Ganesh, incoming Ph.D. student at the University of Montreal and Mila; interested in studying the learning dynamics of neural networks at the intersection of fairness, robustness, privacy, … [Read more...] about On the Impact of Machine Learning Randomness on Group Fairness
Labour
Enough With “Human-AI Collaboration”
🔬 Research Summary by Advait Sarkar, an affiliate lecturer at the University of Cambridge, and honorary lecturer at UCL. [Original paper by Advait Sarkar] Overview: The term "human-AI collaboration" is … [Read more...] about Enough With “Human-AI Collaboration”
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
🔬 Research Summary by Zeqiu Wu and Yushi Hu Zeqiu Wu is a final-year PhD student at University of Washington, where she works on language models that converse with and learn from information-seeking … [Read more...] about Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Whose AI Dream? In search of the aspiration in data annotation.
🔬 Research Summary by Ding Wang, a senior researcher from the Responsible AI Group in Google Research, specializing in responsible data practices with a specific focus on accounting for the human experience and … [Read more...] about Whose AI Dream? In search of the aspiration in data annotation.
A roadmap toward empowering the labor force behind AI
🔬 Research summary by Hanlin Li, Nicholas Vincent, Stevie Chancellor, and Brent Hecht. Hanlin Li is a postdoc at UC Berkeley and an incoming assistant professor at UT Austin. Nicholas Vincent is an assistant … [Read more...] about A roadmap toward empowering the labor force behind AI