**1. Introduction**

What is artificial intelligence (AI)? There is no direct definition of AI or a consensus thereon, and AI is often understood as a set of techniques designed to use machines to approximate certain aspects of human or animal cognition. Early theorists believed that the symbolic system (the organization of

abstract symbols using logical rules) was the most productive way to pursue a computer that could "think"; however, as originally unimagined by Turing and others, the strategy of constructing an inference engine did not achieve the initial cognitive tasks, and it seemed that the theoretically possible concepts had not produced many feasible applications in practice [1]. Li and Wang gave five common definitions of artificial intelligences (AI) in their book *Artificial Intelligence*: (1) AI is a computer program which makes people feel inconceivable; (2) AI is a computer program similar to human thinking; (3) AI is a computer program similar to human behavior; (4) AI is a computer program that can learn; (5) AI is a computer program that can make reasonable actions according to the perception of the environment and obtain the most profitable benefits [2]. They believe that the fifth definition relates to the comprehensive definition used by Wikipedia, which offers a relatively recognized, textbook-like definition of the academic world, and it is comprehensively balanced and emphasized. The first few definitions are from the perspective of public, pragmatism, or machine learning. The perspective of trends it is not comprehensive enough and slightly biased; of course, AI is a field with a wide range of meaning and rich enrichment, and it is necessary for the scientific community and society to continue to extend, expand, and apply its connotations and denotations [2]. Some scholars believe that AI is the intelligent simulation of human behavior through the use of advanced technology, and that the process involves extremely complex human–machine relationships; from the perspective of information perception, data management, deep learning, bionic behavior, and language interaction, AI includes five core elements: cross media perceptual computing, autonomous deep learning, big data intelligent management, virtualized bionics, and simulated language interaction [3].

The research of artificial intelligence has attracted the attention of many scholars, and many fields involves the application of artificial intelligence, machine learning, and pattern recognition, etc. There are published studies and applications involving data transmission, pattern recognition, behavioral research, robotics, and computer engineering [4–8], as well as research and applications in physical sciences, health-related issues, natural sciences, and industrial academic areas [9–11]. Furthermore, there have also been some studies related to applications of different sensors, such as binary, digital cameras, depth data, and wearable sensors, that use AI and data classification fields [12–18].

The latest *China AI Development Report 2018* proposed that the two main lines of development of AI core technologies are brain science and brain-like intelligence technology, and machine learning represented by deep neural networks; currently, brain science and brain-like intelligence technology research progress is limited. Machine learning is developing rapidly, and has become the mainstream paradigm of AI technology today; people often even equate the concepts of "AI" and "machine learning"; in general, the AI we know today is based on modern algorithms and supported by historical data to form artificial programs or systems that can perceive, recognize, make decisions, and execute actions like human beings [19].

Discussions and studies on AI were published in *Sciences*, *Artificial Intelligence*, and other important academic journals in 1980s and 1990s. At that time, most of them discussed the relationship between AI and computer information processing, and the significance of AI for future innovation and new ideas [20,21]. Boden believed that AI could simulate and realize the creativity of human intelligence in the future [21]. Since the beginning of the new century, research into and application of AI has become more and more abundant, rapid, and in-depth, and it has played an increasingly obvious role in promoting scientific and technological innovation and economic and social development; especially in the past decade, artificial intelligence has garnered a considerable amount of attention from academia and governments of many countries and regions. Scholars' research keeps pace with contemporary trends and benefits from the government's policy guidance and promotion; meanwhile, the research and application of new technology and AI has a significant role in promoting the development of countries and societies [22–26].

A considerable number of scholars have been engaged in research on big data, data mining, smart city, education, knowledge management, innovation network, policy-making, and other areas

related to AI, as well as many journal articles, research topics, and research conferences on AI [25–35]. The special issue on "Human Centered Web Science" from the journal *World Wide Web* is to explore how humans could keep up with the current trend toward authorizing users to collectively decide on the usage of web-based information and services in the new era of Internet and AI, and to study and discuss how to master human-driven features of Web-based systems, conduct high-level governance policies and so on [36]. These studies discuss how to adapt to the new era and new trends, and explore the corresponding ideas and solutions. The special issue "Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness" of the journal *Sustainability* is another typical representation [37]. A considerable number of articles have explored the new era of big data, knowledge management, and innovation. Integration would result in policy driven at a higher level of abstraction; many related scholars believe that the diffusion and development of these multidisciplinary characters and innovations will be based on critical and radical diffusions of smart machines and AI. This research was based on the special issue "Artificial Intelligence and Cognitive Computing: Methods, Technologies, Systems, Applications and Policy Making", and explored the interactive relationship between the hotspots of China's AI international research and national-level policy keywords.

Many scholars have explored the diverse effects, problems, and implications of AI. From the perspective of social science, Miller combed and proposed the development of interpretable artificial intelligence [38]. Lytras, Hassan, and Aljohani believed that in a new era of collective human wisdom, the intelligent library would be one of the important representations and composition systems of AI and the smart city; this kind of personalized and intelligent service and technology-integrated data mining, scientometrics, computer science, AI, and other technologies, and, in the future, library and information science, combined with AI, smart cities and other concepts could help humans to better make scientific and sensible decisions in the face of complex networks and big data [39]. Rajan and Saffiotti discussed the development status and practice of the emerging field of integrated AI and Robotics [40]. Chui, Lytras, and Visvizi discussed the various ways in which AI and big data could offer important support during the process of attaining energy sustainability in smart cities [41].

Some scholars have discussed the impact of AI on scientific research, the expansion of scientific discoveries, and the economic impact of AI in last few years [42,43]. Visvizi, Lytras, and co-workers conducted research on smart cities, big data, education, knowledge management, and AI, explored the comprehensive impact of related technology and service, and discussed the relationship between policy-making and academic research, focusing on existing research and technological innovation [44–47]. In recent years, AI has gradually become a national strategy in China, and relevant policies and designs at the central and local levels have been introduced. Chinese scholars' research on domestic and international AI applications has gradually deepened and expanded. This research includes not only the comprehension of relevant policies and industrial trends of AI in China [19,48–51] and the comparative analysis of AI development strategies and situations domestically and abroad [52–54], but also the discussion of AI development and application to specific fields [55–57]. Over the past five years, more articles have been published on the internal and external governance, construction path and social impact of AI [58–60]; meanwhile, more and more econometric analyses have been conducted in certain fields of AI [61–63].

In general, there are two parts to the research into China's AI policy and China's AI research hotspot. The first part is the research on AI policy. For example, some scholars have discussed the policy quantification of AI [63,64], and there are studies on the development policy and strategic layout of China and other countries in the overall field or specific field of AI [53,65–67]. The other part is research on the field and hotspots of artificial intelligence research in China, such as the analysis of the academic pedigree of scholars in the field of AI research [63], and the comparative study of research hot spots and frontier trends between China and other countries [68], but the comparative study of Chinese academic research hotspots and political policy priorities has been relatively sparse.

As some members of the China AI Development Report 2018 research group, the team of this research participated in the sorting and analysis of the policy part of the report. After the completion of the report, the team members wanted to further explore the relationships and interactions between the content of China's AI policy concerns and Chinese scholars' research concerns, hoping to further enrich such comparative studies and provide corresponding suggestions to political and academic circles.

This research was based on Chinese scholars' international research on artificial intelligence and the relevant hotspots, keywords in English articles, and the comparison of hotspots and keywords in Chinese government policy literature. By tracing the hot topics and key words of Chinese scholars' international studies and domestic political circles, this study was able to track the interaction between domestic policies and international research, and then provide certain implications, references, and theoretical bases for the internationalization of AI research in China, the internationalization of relevant domestic policies, and the relationship between academia and policies.
