Artificial Intelligence is a field that lives many lives, and the term has come to encompass a motley collection of scientific and commercial endeavours. In this paper, I articulate the contours of a rather neglected but central scientific role that AI has to play, which I dub `AI-as-exploration'.The basic thrust of AI-as-exploration is that of creating and studying systems that can reveal candidate building blocks of intelligence that may differ from the forms of human and animal intelligence we are familiar with. In other words, I suggest that AI is one of the best tools we have for exploring intelligence space, namely the space of possible intelligent systems. I illustrate the value of AI-as-exploration by focusing on a specific case study, i.e., recent work on the capacity to combine novel and invented concepts in humans and Large Language Models. I show that the latter, despite showing human-level accuracy in such a task, most probably solve it in ways radically different, but no less relevant to intelligence research, to those hypothesised for humans.

翻译：人工智能是一个承载着多重使命的领域，该术语已涵盖众多科学和商业活动。本文旨在阐述人工智能在科学领域中一个常被忽视却至关重要的角色，我将其称为“AI作为探索”。AI作为探索的基本思路在于，通过创造并研究系统，揭示那些可能异于我们熟悉的人类及动物智能形式的智能构建基础。换言之，我认为人工智能是探索智能空间（即所有可能的智能系统所构成的空间）的最佳工具之一。通过聚焦于一个具体案例——即近期关于人类与大语言模型在组合新颖及虚构概念能力方面的研究——我阐明了AI作为探索的价值。研究表明，尽管大语言模型在此类任务中展现出与人类相当的水平，但其解题方式很可能与人类假设的机制截然不同，然而这种差异对智能研究同样具有重要意义。