219 citations · 257 across the 6 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CY2023★ 5 cited
Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives
Elizabeth Seger, Noemi Dreksler, Richard Moulange +19
Recent decisions by leading AI labs to either open-source their models or to restrict access to their models has sparked debate about whether, and how, increasingly capable AI mode…
cs.AI2023★ 13 cited
Democratising AI: Multiple Meanings, Goals, and Methods
Elizabeth Seger, Aviv Ovadya, Ben Garfinkel +2
Numerous parties are calling for the democratisation of AI, but the phrase is used to refer to a variety of goals, the pursuit of which sometimes conflict. This paper identifies fo…