常进,宋轶晗,杜冰,邬科飞,罗阿理,刘继峰.人工智能赋能天文学战略机遇、政策挑战与发展路径[J].中国科学院院刊,2026,41(6):1162-1168.

人工智能赋能天文学战略机遇、政策挑战与发展路径

Artificial intelligence for astronomy: Strategic opportunities, policy challenges and development strategies

常进^1*
中国科学技术大学 合肥 230026
CHANG Jin^1*
University of Science and Technology of China, Hefei 230026, China
宋轶晗²
中国科学院国家天文台 北京 100101
SONG Yihan²
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
杜冰²
中国科学院国家天文台 北京 100101
DU Bing²
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
邬科飞²
中国科学院国家天文台 北京 100101
WU Kefei²
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
罗阿理²
中国科学院国家天文台 北京 100101
LUO Ali²
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
刘继峰²
中国科学院国家天文台 北京 100101
LIU Jifeng²
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China

         人工智能;天文学;深度融合;大科学设施;政策路径

        artificial intelligence;astronomy;deep integration;large-scale scientific facilities;policy pathways

        人工智能与天文学的深度融合正引发全球基础科学研究范式变革，成为关乎国家科技竞争、战略安全与产业升级的重大命题。文章立足我国郭守敬望远镜 （LAMOST）、500米口径球面射电望远镜 （“中国天眼”，FAST）、高海拔宇宙线观测站 （拉索，LHAASO） 等地面大科学设施，以及中国巡天空间望远镜（CSST）、“天关”（EP）、“慧眼”（Insight-HXMT）、“悟空”（DAMPE）等空间望远镜优势，采用系统分析与路径比较方法，系统研判“天文+人工智能”（“天文+AI”） 融合发展的政策需求、现实短板与可行路径。研究表明，全球已进入模型驱动的智能天文新阶段，美欧率先完成战略布局；我国虽取得阶段性突破，但仍面临多模态数据治理滞后、跨学科协同不足、智能化观测响应能力弱、AI模型可解释性欠缺四大核心短板。文章提出国家专项主导、产学研协同开放、国际合作嵌入3条政策路径，经综合评估确立最优方案为“国家专项筑基、产学研协同赋能、国际合作补位”的协同推进模式。最后从地面与空间设施、算法、人才、产业四维联动角度提出融合创新体系建设路径，为提升我国天文AI全球竞争力、支撑基础科学发展与国家科技战略安全提供政策参考。

        To alleviate the bottlenecks hindering the integrated development of artificial intelligence and astronomy in China and to reinforce the country’s strategic edge in science and technology, this study uses systematic analysis and path-comparison approaches to examine the policy requirements for their deep integration. The findings indicate that this topic is closely tied to global competition in science and technology, strategic security, and industrial upgrading. At present, the world has entered a new “astronomy + AI” paradigm, with the United States and the European Union already having taken the lead in establishing corresponding strategic frameworks. Leveraging major scientific infrastructures such as FAST, LAMOST, LHAASO, CSST, EP, Insight-HXMT, and DAMPE, China has made staged advances, yet it still faces four key weaknesses, including delayed progress in multi-modal data governance, insufficient interdisciplinary collaboration, weak intelligent observation and response capacity, and lack of interpretability for AI models. In response, this study outlines three policy pathways and, following a comprehensive assessment, identifies the optimal route as a coordinated promotion model that rests on “national special projects as the cornerstone, industry–academia–research collaboration as the main driver, and international cooperation as a complementary force.” Consequently, it is essential to construct an integrated innovation system that realizes four-dimensional linkage among facilities, algorithms, talent, and industry, with the aim of addressing existing development gaps, bolstering China’s competitiveness in the global astronomical AI arena, and underpinning both basic scientific progress and the nation’s science-and-technology strategic security.