人工智能赋能高校数据治理:逻辑、挑战与实践

随着人类社会逐步迈入以情感计算、自然语言处理等智能技术为核心支撑的人工智能时代,数据的战略资源地位日益凸显,数据治理已成为推进高校教育治理现代化的关键工具。人工智能赋能高校数据治理的基本逻辑主要体现在数据管理、数据质量、数据决策与数据服务4个层面。高校数据管理忽视“多方协同管理”、缺乏相对统一的数据质量标准、数据决策在权责限定与顶层设计方面存在缺失、数据服务潜能激发不力制约数据价值高效释放等可被视为人工智能赋能高校数据治理的现实挑战。对此,应创设落位智能共管的高校数据管理职能优化机制、完善校本化高校数据挖掘与共享质量标准、构建基于责权厘定的智能化数据决策体系、优化指向数据价值释放的智能数据服务体系。

Artificial Intelligence Enables Data Governance in Universities:Logic,Challenge and Practice

With human society gradually entering the era of artificial intelligence with intelligent technologies such as emotional computing and natural language processing as the core support,the strategic resource status of data has become increasingly prominent,and the data governance has become a key tool to promote the modernization of educational governance in colleges and universities.The basic logic of AI enabling university data governance is mainly reflected in four levels:data management,data quality,data decision-making and data service.The neglect of“multi-party collaborative management”in university data management,the lack of relatively unified data quality standards,the lack of power and responsibility limitation and top-level design in data decision-making,and the weak stimulation of data service potential restricting the efficient release of data value can be regarded as the practical challenges of AI enabling university data governance.Therefore,an optimization mechanism of university data management function with intelligent co-management should be created,the quality standard of school-based university data mining and sharing to be improved,an intelligent data decision-making system to be built based on the responsibility and power,and the intelligent data service system pointing to the release of data value to be optimized.