4 papers · 1 filter
If open source is to win, it must go public
Joshua Tan, Nicholas Vincent, Katherine Elkins +5
Open source projects have made incredible progress in producing widely usable machine learning models and systems, but open source alone will face challenges in fully democratizing…
Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
Nicholas Vincent, Matthew Prewitt, Hanlin Li
This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as…
AI for Just Work: Constructing Diverse Imaginations of AI beyond "Replacing Humans"
Weina Jin, Nicholas Vincent, Ghassan Hamarneh
"why" we develop AI. Lacking critical reflections on the general visions and purposes of AI may make the community vulnerable to manipulation. In this position paper, we explore th…
An Alternative to Regulation: The Case for Public AI
Nicholas Vincent, David Bau, Sarah Schwettmann +1
Can governments build AI? In this paper, we describe an ongoing effort to develop ``public AI'' -- publicly accessible AI models funded, provisioned, and governed by governments or…