no code implementations • 27 Feb 2024 • Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan
To understand their risks of misuse, we design a risk assessment framework for analyzing their marginal risk.
no code implementations • 24 Jan 2023 • Aspen Hopkins, Fred Hohman, Luca Zappella, Xavier Suau Cuadros, Dominik Moritz
Lack of diversity in data collection has caused significant failures in machine learning (ML) applications.
no code implementations • 6 Oct 2021 • Aspen Hopkins, Serena Booth
Practitioners from diverse occupations and backgrounds are increasingly using machine learning (ML) methods.