| 葛 川 陈洪梅 杨 莹.人工智能驱动科学研究范式下区域科技资源配置优化路径研究——以苏州市为例[J].中国科技资源导刊,2025,(6):91~99 |
| 人工智能驱动科学研究范式下区域科技资源配置优化路径研究——以苏州市为例 |
| Optimization Pathways for Regional Sci-Tech Resource Allocation under the AI for Science Paradigm: A Case Study of Suzhou City |
| 投稿时间：2025-11-07 |
| DOI： |
| 中文关键词: 人工智能驱动的科学研究;区域创新生态;技术可供性;制度逻辑;科技资源配 |
| 英文关键词: AI for science, regional innovation ecosystem, technology affordance; institutional logic, science and technology resource allocation |
| 基金项目: |
| 作者 | 单位 | | 葛 川 陈洪梅 杨 莹 | (苏州市科技服务中心(苏州市科学技术情报研究所)，江苏苏州 215011) |
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| 中文摘要: |
| 人工智能驱动的科学研究(AI4S)正引发科研范式变革，对区域科技资源配置提出新的挑战。以苏州市为例，基于技术可供性与制度逻辑双重视角，剖析区域创新生态演进的动力机制与制约因素。研究发现，苏州面临数据孤岛顽固、算力结构性错配、原创基座模型缺位等困境，其根源在于公立机构的风险规避倾向、私营企业的竞争壁垒以及金融资本的短期导向与AI4S研发需求之间的制度冲突。通过对比美国“公私协同”与日本“虚拟连接”模式，提出从“物理堆砌”向“制度耦合”转型的路径建议，即构建数据信托机制破解信任赤字、设立长周期资本专项弥合时空错配、打造云端验证闭环重构创新流程，以推动区域科技资源从要素集聚向生态配置跃迁。 |
| 英文摘要: |
| AI for Science (AI4S) is triggering a paradigm shift in scientific research, presenting new challenges for the allocation of regional science and technology resources. Taking Suzhou City as a case study, this paper analyzes the dynamic mechanisms and constraints of the regional innovation ecosystem evolution from the dual perspectives of technology affordance and institutional logic. The study finds that Suzhou faces challenges including persistent data silos, structural mismatches in computing power, and the absence of original foundation models. The root causes in the institutional conflicts between the risk-averse tendencies of public institutions, the competitive barriers of private enterprises, the short-term orientation of financial capital, and the requirements of AI4S R&D. By contrasting the US “public-private collaboration” model and Japan’s “virtual connection” model, this research proposes pathways for transitioning from “physical accumulation” to “institutional coupling.” The proposed suggestions include: establishing a data trust mechanism to break down the trust deficit, setting up dedicated long-term capital funds to bridge temporal and spatial mismatches, and building a cloud-based verification closed-loop to reconstruct innovation processes, thereby promoting the transition of science and technology resources from factor accumulation to ecological allocation. |
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