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The AI techno-economic complex System: Worldwide landscape, thematic subdomains and technological collaborations

工件(错误) 数据科学 订单(交换) 计算机科学 现象 鉴定(生物学) 商品和服务 空格(标点符号) 工作(物理) 专题地图 业务 人工智能 区域科学 社会学 经济 经济 地理 工程类 地图学 认识论 哲学 财务 生物 操作系统 机械工程 植物
作者
Riccardo Righi,Sofia Samoili,Montserrat López Cobo,Miguel Vazquez‐Prada Baillet,Melisande Cardona,Giuditta De Prato
出处
期刊:Telecommunications Policy [Elsevier BV]
卷期号:44 (6): 101943-101943 被引量:24
标识
DOI:10.1016/j.telpol.2020.101943
摘要

Artificial intelligence (AI) is playing a major role in the new paradigm shift occurring across the technological landscape. After a series of alternate seasons starting in the 60s, AI is now experiencing a new spring. Nevertheless, although it is spreading throughout our economies and societies in multiple ways, the absence of standardised classifications prevents us from obtaining a measure of its pervasiveness. In addition, AI cannot be identified as part of a specific sector, but rather as a transversal technology because the fields in which it is applied do not have precise boundaries. In this work, we address the need for a deeper understanding of this complex phenomenon by investigating economic agents' involvement in industrial activities aimed to supply AI-related goods and services, and AI-related R&D processes in the form of patents and publications. In order to conduct this extensive analysis, we use a complex systems approach through the agent-artifact space model, which identifies the core dimensions that should be considered. Therefore, by considering the geographic location of the involved agents and their organisation types (i.e., firms, governmental institutions, and research institutes), we (i) provide an overview of the worldwide presence of agents, (ii) investigate the patterns in which AI technological subdomains subsist and scatter in different parts of the system, and (iii) reveal the size, composition, and topology of the AI R&D collaboration network. Based on a unique data collection of multiple micro-based data sources and supported by a methodological framework for the analysis of techno-economic segments (TES), we capture the state of AI in the worldwide landscape in the period 2009–2018. As expected, we find that major roles are played by the US, China, and the EU28. Nevertheless, by measuring the system, we unveil elements that provide new, crucial information to support more conscious discussions in the process of policy design and implementation.

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