提出应以人类和动物智能为参照，重新审视对AGI安全的期待。
Position Paper: Bounded Alignment: What (Not) To Expect From AGI Agents
- 以生物智能为基准重构对AGI的认知框架
- 批判当前对通用智能的过度乐观预期
- 适合关注AI安全与政策制定的研究者
随着人工通用智能（AGI）的前景日益临近，人工智能风险与安全问题变得愈发关键。超大规模生成模型的出现引发了从董事会到立法机构的广泛关注与担忧，促使人工智能对齐（AI alignment）成为人工智能研究中最重要领域之一。本文主张，当前人工智能与机器学习社区对AGI的主流愿景亟需调整，对安全性的期望与评估标准必须更多基于我们对唯一已知的通用智能实例——即动物和人类智能——的理解。这一视角转变将带来更现实的技术认知，有助于制定更科学的政策决策。
原文摘要 · Abstract (English)
The issues of AI risk and AI safety are becoming critical as the prospect of artificial general intelligence (AGI) looms larger. The emergence of extremely large and capable generative models has led to alarming predictions and created a stir from boardrooms to legislatures. As a result, AI alignment has emerged as one of the most important areas in AI research. The goal of this position paper is to argue that the currently dominant vision of AGI in the AI and machine learning (AI/ML) community needs to evolve, and that expectations and metrics for its safety must be informed much more by our understanding of the only existing instance of general intelligence, i.e., the intelligence found in animals, and especially in humans. This change in perspective will lead to a more realistic view of the technology, and allow for better policy decisions.
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