As AI systems appear to exhibit ever-increasing capability and generality, assessing their true potential and safety becomes paramount. This paper contends that the prevalent evaluation methods for these systems are fundamentally inadequate, heightening the risks and potential hazards associated with AI. I argue that a reformation is required in the way we evaluate AI systems and that we should look towards cognitive sciences for inspiration in our approaches, which have a longstanding tradition of assessing general intelligence across diverse species. We will identify some of the difficulties that need to be overcome when applying cognitively-inspired approaches to general-purpose AI systems and also analyse the emerging area of "Evals". The paper concludes by identifying promising research pathways that could refine AI evaluation, advancing it towards a rigorous scientific domain that contributes to the development of safe AI systems.

翻译：随着人工智能系统展现出日益增强的能力与通用性，评估其真实潜力与安全性变得至关重要。本文认为，当前对这些系统的主流评估方法存在根本性不足，加剧了AI相关的风险与潜在危害。作者主张，我们需要改革AI系统的评估方式，并应从认知科学中汲取方法论灵感——该领域长期致力于评估不同物种的通用智能。我们将指出将认知启发式方法应用于通用AI系统时需要克服的若干困难，同时分析新兴的"评估学"领域。最后，本文提出若干具有前景的研究路径，以期完善AI评估体系，推动其发展成为能够促进安全AI系统开发的严谨科学领域。