Fei-Fei Li's Briefing to the United Nations Security Council
In this address, presented to the United Nations Security Council meeting on "Maintenance of International Peace and Security and Artificial Intelligence," Fei-Fei Li stresses the importance of public sector leadership, global collaboration, and evidence-based policymaking to unlock AI’s potential and ensure its responsible development.
Related Publications
In this address, presented to the United Nations Security Council meeting on "Maintenance of International Peace and Security," Yejin Choi calls on the global scientific and policy communities to expand the AI frontier for all by pursuing intelligence that is not only powerful, but also accessible, robust, and efficient. She stresses the need to rethink our dependence on massive-scale data and computing resources from the outset, and design methods that do more with less — by building AI that is smaller and serves all communities.
In this address, presented to the United Nations Security Council meeting on "Maintenance of International Peace and Security," Yejin Choi calls on the global scientific and policy communities to expand the AI frontier for all by pursuing intelligence that is not only powerful, but also accessible, robust, and efficient. She stresses the need to rethink our dependence on massive-scale data and computing resources from the outset, and design methods that do more with less — by building AI that is smaller and serves all communities.
This brief presents an analysis of Chinese AI startup DeepSeek’s talent base and calls for U.S. policymakers to reinvest in competing to attract and retain global AI talent.
This brief presents an analysis of Chinese AI startup DeepSeek’s talent base and calls for U.S. policymakers to reinvest in competing to attract and retain global AI talent.
Mind the (Language) Gap: Mapping the Challenges of LLM Development in Low-Resource Language Contexts
This white paper maps the LLM development landscape for low-resource languages, highlighting challenges, trade-offs, and strategies to increase investment; prioritize cross-disciplinary, community-driven development; and ensure fair data ownership.
Mind the (Language) Gap: Mapping the Challenges of LLM Development in Low-Resource Language Contexts
This white paper maps the LLM development landscape for low-resource languages, highlighting challenges, trade-offs, and strategies to increase investment; prioritize cross-disciplinary, community-driven development; and ensure fair data ownership.
Escalation Risks from LLMs in Military and Diplomatic Contexts
This brief presents the results of a wargame simulation that aims to evaluate the escalation risks of large language models (LLMs) in high-stakes military and diplomatic decision-making.
This brief presents the results of a wargame simulation that aims to evaluate the escalation risks of large language models (LLMs) in high-stakes military and diplomatic decision-making.