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The AI techno-economic complex System: Worldwide landscape, thematic subdomains and technological collaborations
سیستم پیچیده فنی اقتصادی هوش مصنوعی : چشم انداز جهانی ، زیر دامنه های موضوعی و همکاری های فناوری-2020 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. Keywords: Artificial intelligence | Complex systems | Agent-artifact space | Natural language processing | Semantic analysis | Network analysis |
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