To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier risks. Drawing on the E-T-C analysis (deployment environment, threat source, enabling capability) from the Frontier AI…
Shanghai AI Laboratory and Concordia AI are proud to introduce the Frontier AI Risk Management Framework v1.0 (the “Framework”). We propose a robust set of protocols designed to empower general-purpose AI developers with comprehensive guidelines for proactively identifying, assessing, mitigating,…
The report, Responsible Innovation in AI x Life Sciences (人工智能 x 生命科学的负责任创新), is a collaborative publication by Concordia AI and the Center for Biosafety Research and Strategy of Tianjin University. The report explores the convergence of artificial intelligence and the…
As artificial intelligence systems grow more powerful and integrated into society, their safe development presents a critical governance challenge. This report, led by Concordia AI, the Oxford Martin AI Governance Initiative, and Carnegie Endowment for International Peace, examines whether framing…
On December 16, 2024, the World Economic Forum white paper "Navigating the AI Frontier: A Primer on the Evolution and Impact of AI Agents," in which Concordia AI participated, was officially released. The white paper explores the development of AI…
On April 27, 2024, the 2024 Zhongguancun Forum AGI Conference was held at the Zhongguancun National Innovation Demonstration Zone Conference Center. The forum was hosted by the Beijing Municipal Science and Technology Commission, the Zhongguancun Science Park Administrative Committee, and…
The 2023 International AI Cooperation and Governance Forum, co-organized by Tsinghua University and the Hong Kong University of Science and Technology (HKUST), was held at HKUST on December 8-9, 2023. Concordia AI co-hosted and moderated the "Frontier AI Safety and…
The research team from Peking University, in collaboration with researchers from multiple universities both domestically and internationally, has released a comprehensive survey on AI alignment, covering four core issues for achieving AI alignment: "Learning from Feedback," "Learning under Distributional Shift,"…
The research team from Peking University, in collaboration with researchers from multiple universities both domestically and internationally, has released a comprehensive survey on AI alignment, covering four core issues for achieving AI alignment: "Learning from Feedback," "Learning under Distributional Shift,"…