🔬 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
Fairness
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
ChatGPT and the media in the Global South: How non-representative corpus in sub-Sahara Africa are engaging with the chatbots
🔬 Research Summary by Gregory Gondwe, an Assistant Professor of Journalism at California State University – San Bernardino and a Harvard faculty Associate with the Berkman Klein Centre. [Original paper by … [Read more...] about ChatGPT and the media in the Global South: How non-representative corpus in sub-Sahara Africa are engaging with the chatbots
Does diversity really go well with Large Language Models?
✍️ Column by Sun Gyoo Kang, Lawyer. Disclaimer: The views expressed in this article are solely my own and do not reflect my employer's opinions, beliefs, or positions. Any opinions or information in this article … [Read more...] about Does diversity really go well with Large Language Models?