評估危險能力的前沿模型

Evaluating Frontier Models for Dangerous Capabilities

March 20, 2024

作者: Mary Phuong, Matthew Aitchison, Elliot Catt, Sarah Cogan, Alexandre Kaskasoli, Victoria Krakovna, David Lindner, Matthew Rahtz, Yannis Assael, Sarah Hodkinson, Heidi Howard, Tom Lieberum, Ramana Kumar, Maria Abi Raad, Albert Webson, Lewis Ho, Sharon Lin, Sebastian Farquhar, Marcus Hutter, Gregoire Deletang, Anian Ruoss, Seliem El-Sayed, Sasha Brown, Anca Dragan, Rohin Shah, Allan Dafoe, Toby Shevlane

cs.AI

摘要

為了了解一個新的人工智慧系統可能帶來的風險，我們必須了解它的能力和限制。在先前的工作基礎上，我們引入了一個新的「危險能力」評估計劃，並在 Gemini 1.0 模型上進行試點。我們的評估涵蓋四個領域：(1) 說服和欺騙；(2) 網絡安全；(3) 自我擴散；以及 (4) 自我推理。我們並未在評估的模型中發現強烈的危險能力證據，但我們標記了早期警示信號。我們的目標是推動一個嚴謹的危險能力評估科學，為未來的模型做好準備。

English

To understand the risks posed by a new AI system, we must understand what it can and cannot do. Building on prior work, we introduce a programme of new "dangerous capability" evaluations and pilot them on Gemini 1.0 models. Our evaluations cover four areas: (1) persuasion and deception; (2) cyber-security; (3) self-proliferation; and (4) self-reasoning. We do not find evidence of strong dangerous capabilities in the models we evaluated, but we flag early warning signs. Our goal is to help advance a rigorous science of dangerous capability evaluation, in preparation for future models.