12 citations · 33 across the 6 of their papers we have counts for
3 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…
Comparative Global AI Regulation: Policy Perspectives from the EU, China, and the US
Jon Chun, Christian Schroeder de Witt, Katherine Elkins
As a powerful and rapidly advancing dual-use technology, AI offers both immense benefits and worrisome risks. In response, governing bodies around the world are developing a range…
Informed AI Regulation: Comparing the Ethical Frameworks of Leading LLM Chatbots Using an Ethics-Based Audit to Assess Moral Reasoning and Normative Values
Jon Chun, Katherine Elkins
With the rise of individual and collaborative networks of autonomous agents, AI is deployed in more key reasoning and decision-making roles. For this reason, ethics-based audits pl…