🔬 Research Summary by Laurence Barry and Arthur Charpentier. Laurence Barry is an independent actuary and a researcher at PARI (Programme de Recherche sur l’Appréhension des Risques et des Incertitudes, ENSAE/ … [Read more...] about Melting contestation: insurance fairness and machine learning
Bias Mitigation
An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature
🔬 Research Summary by Amina Abdu, a Ph.D. candidate at the University of Michigan School of Information, where she researches how computational tools shape policy decisions. [Original paper by Amina A. Abdu, … [Read more...] about An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature
Public Perceptions of Gender Bias in Large Language Models: Cases of ChatGPT and Ernie
🔬 Research Summary by Kyrie Zhixuan Zhou and Madelyn Rose Sanfilippo. Kyrie Zhixuan Zhou is a PhD student at the University of Illinois at Urbana-Champaign, aiming to understand, design, and govern ICT/AI … [Read more...] about Public Perceptions of Gender Bias in Large Language Models: Cases of ChatGPT and Ernie
A Sequentially Fair Mechanism for Multiple Sensitive Attributes
🔬 Research Summary by Francois Hu & Philipp Ratz. François Hu is a postdoctoral researcher in statistical learning at UdeM in Montreal. Philipp Ratz is a PhD student at UQAM in Montreal. [Original … [Read more...] about A Sequentially Fair Mechanism for Multiple Sensitive Attributes
Bias Propagation in Federated Learning
🔬 Research Summary by Hongyan Chang, a sixth-year Ph.D. student at the National University of Singapore, focuses on algorithmic fairness and privacy, particularly their intersection, and is also invested in advancing … [Read more...] about Bias Propagation in Federated Learning