1 code implementation • 15 Apr 2024 • Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwan, Yoshua Bengio, Danqi Chen, Philip H. S. Torr, Samuel Albanie, Tegan Maharaj, Jakob Foerster, Florian Tramer, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
This work identifies 18 foundational challenges in assuring the alignment and safety of large language models (LLMs).
no code implementations • 28 Sep 2019 • Javier Sanchez-Monedero, Lina Dencik, Lilian Edwards
The ability to get and keep a job is a key aspect of participating in society and sustaining livelihoods.
no code implementations • 12 Jul 2018 • Michael Veale, Reuben Binns, Lilian Edwards
Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms.
no code implementations • 20 Mar 2018 • Lilian Edwards, Michael Veale
As concerns about unfairness and discrimination in "black box" machine learning systems rise, a legal "right to an explanation" has emerged as a compellingly attractive approach for challenge and redress.
