摘要
[研究目的]场景驱动是本轮人工智能发展热潮的重要特征之一,对人工智能应用场景成熟度进行评价研究,有助于更好地研判应用场景所处的状态或发展阶段,进而探讨各种因素对这一状态或阶段的影响程度。[研究方法]研究提出人工智能应用场景成熟度评价模型,将人工智能应用场景成熟度划分为人因成熟度、技术成熟度和环境成熟度,构建了包括需求迫切性、安全保证性等10个二级指标和高被引论文、支持政策等21个三级指标在内的评价指标体系。[研究结论]应用该模型对我国国家新一代人工智能创新发展试验区所在地区智能医疗场景的成熟度进行评价,结果发现当前广东、浙江、北京和上海智能医疗场景成熟度最高,山东、天津等的成熟度处在中等水平,重庆、陕西和四川成熟度相对较低。
[Research purpose]Context-driven is one of the important characteristics of the current wave of artificial intelligence development.Evaluation and research on the maturity of artificial intelligence application contexts will help to better judge the state or development stage of the application scenario,and further explore the effects of various factors on the degree of influence of this state or stage.[Research method]This paper studies and proposes a maturity evaluation model for artificial intelligence application contexts,which divides the maturity of artificial intelligence application contexts into human maturity,technology maturity,and environmental maturity,and constructs 10 secondary indicators including demand urgency,safety assurance,etc.An evaluation index system including 21 three-level indicators such as highly cited papers and supporting policies is also integrated into the model.[Research conclusion]The model is used to evaluate the maturity of smart medical scenarios in the areas where China's national new-generation artificial intelligence innovation and development pilot zones are located.The highest maturity of the current smart medical contexts is found in Guangdong,Zhejiang,Beijing and Shanghai,the moderate level of maturity is in Shandong,Tianjin,etc.,and the relatively low maturity is in Chongqing,Shaanxi and Sichuan.
作者
李梦薇
高芳
徐峰
Li Mengwei;Gao Fang;Xu Feng(China Institute of Scientific and Technical Information,Beijing 100038)
出处
《情报杂志》
CSSCI
北大核心
2022年第12期176-183,共8页
Journal of Intelligence
基金
科技创新2030-“新一代人工智能”重大项目“重点领域人工智能治理挑战及对策研究”(编号:2020AAA0105300)子课题“重点领域人工智能伦理风险及对策研究”(编号:2020AAA0105301)研究成果之一。
关键词
人工智能
应用场景
成熟度评价
智能医疗
试验区
artificial intelligence
application context
maturity evaluation
intelligent medical care
pilot zone