The scientific method is the cornerstone of human progress across all branches of the natural and applied sciences, from understanding the human body to explaining how the universe works. The scientific method is based on identifying systematic rules or principles that describe the phenomenon of interest in a reproducible way that can be validated through experimental evidence. In the era of artificial intelligence (AI), there are discussions on how AI systems may discover new knowledge. We argue that human complex reasoning for scientific discovery remains of vital importance, at least before the advent of artificial general intelligence. Yet, AI can be leveraged for scientific discovery via explainable AI. More specifically, knowing what data AI systems deemed important to make decisions can be a point of contact with domain experts and scientists, that can lead to divergent or convergent views on a given scientific problem. Divergent views may spark further scientific investigations leading to new scientific knowledge.

翻译：科学方法是人类在自然科学与应用科学各领域取得进步的基石，从理解人体结构到阐释宇宙运行规律皆然。科学方法建立在识别系统性规则或原理的基础上，这些规则或原理能以可复现的方式描述目标现象，并可通过实验证据进行验证。在人工智能时代，学界持续探讨AI系统如何可能发现新知识。我们认为，至少在通用人工智能出现之前，人类用于科学发现的复杂推理能力仍具有至关重要的意义。然而，通过可解释人工智能技术，我们能够借助AI推动科学发现。具体而言，了解AI系统决策所依据的关键数据，可以成为领域专家与科学家之间的连接点，从而对特定科学问题产生发散性或聚合性观点。发散性观点可能催生更深入的科学研究，最终引向新的科学认知。