AI让天体物理研究更高效，但需人机协同避免黑箱风险。
AI in the Cosmos
- 用人类知识引导AI，提升模型可解释性与可靠性。
- 实现天体分类、光谱建模等任务的自动化与精准化。
- 适合关注AI伦理与科学可信度的研究者参考。
人工智能正推动科研变革，通过高效分析大规模数据并发现隐藏模式。在天体物理学中，AI已成为关键工具，广泛应用于天体源分类、数据建模及观测结果解读。本文综述了AI在源分类、光谱能量分布建模等方面的应用，并探讨生成式AI带来的新机遇。然而，AI存在偏见、错误和‘黑箱’问题，亟需解决。为此提出人引导人工智能（HG-AI）概念，将人类专业知识融入AI流程，确保其应用具有鲁棒性、可解释性和伦理性，从而深化科学洞察力，推动学术卓越。
原文摘要 · Abstract (English)
Artificial intelligence (AI) is revolutionizing research by enabling the efficient analysis of large datasets and the discovery of hidden patterns. In astrophysics, AI has become essential, transforming the classification of celestial sources, data modeling, and the interpretation of observations. In this review, I highlight examples of AI applications in astrophysics, including source classification, spectral energy distribution modeling, and discuss the advancements achievable through generative AI. However, the use of AI introduces challenges, including biases, errors, and the "black box" nature of AI models, which must be resolved before their application. These issues can be addressed through the concept of Human-Guided AI (HG-AI), which integrates human expertise and domain-specific knowledge into AI applications. This approach aims to ensure that AI is applied in a robust, interpretable, and ethical manner, leading to deeper insights and fostering scientific excellence.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。