Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializers

• URL: http://arxiv.org/abs/2307.10198v1
• Date: Tue, 11 Jul 2023 19:59:54 GMT
• Title: Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializers
• Authors: Chao Min, Yi Zhao, Yi Bu, Ying Ding, Caroline S. Wagner
• Abstract summary: We examine China's AI development process, demonstrating that it is characterized by rapid learning and differentiation. By 2018, the time lag between China and the USA in addressing AI research topics had evaporated. This finding suggests that China has effectively bridged a significant knowledge gap and could potentially be setting out on an independent research trajectory.
• Score: 9.03136346887569
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial Intelligence (AI), a cornerstone of 21st-century technology, has seen remarkable growth in China. In this paper, we examine China's AI development process, demonstrating that it is characterized by rapid learning and differentiation, surpassing the export-oriented growth propelled by Foreign Direct Investment seen in earlier Asian industrializers. Our data indicates that China currently leads the USA in the volume of AI-related research papers. However, when we delve into the quality of these papers based on specific metrics, the USA retains a slight edge. Nevertheless, the pace and scale of China's AI development remain noteworthy. We attribute China's accelerated AI progress to several factors, including global trends favoring open access to algorithms and research papers, contributions from China's broad diaspora and returnees, and relatively lax data protection policies. In the vein of our research, we have developed a novel measure for gauging China's imitation of US research. Our analysis shows that by 2018, the time lag between China and the USA in addressing AI research topics had evaporated. This finding suggests that China has effectively bridged a significant knowledge gap and could potentially be setting out on an independent research trajectory. While this study compares China and the USA exclusively, it's important to note that research collaborations between these two nations have resulted in more highly cited work than those produced by either country independently. This underscores the power of international cooperation in driving scientific progress in AI.

Related papers

• Near to Mid-term Risks and Opportunities of Open-Source Generative AI [94.06233419171016]
  Applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential risks and resulted in calls for tighter regulation. This regulation is likely to put at risk the budding field of open-source Generative AI.
  arXiv  Detail & Related papers  (2024-04-25T21:14:24Z)
• Who is leading in AI? An analysis of industry AI research [0.7839536187821818]
  We compare leading AI companies by research publications, citations, size of training runs, and contributions to algorithmic innovations. Our analysis reveals the substantial role played by Google, OpenAI and Meta. Leading Chinese companies such as Tencent and Baidu had a lower impact on many of these metrics compared to US counterparts.
  arXiv  Detail & Related papers  (2023-11-24T17:36:09Z)
• On the Opportunities of Green Computing: A Survey [80.21955522431168]
  Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades. The needs for high computing power brings higher carbon emission and undermines research fairness. To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
  arXiv  Detail & Related papers  (2023-11-01T11:16:41Z)
• Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 [73.06361680847708]
  In 1960 14% of 333 research fields were related to AI, but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.
  arXiv  Detail & Related papers  (2023-06-15T14:08:07Z)
• China and the U.S. produce more impactful AI research when collaborating together [5.227075179857056]
  We analyze a dataset of over 350,000 AI scientists and 5,000,000 AI papers. We find that since the year 2000, China and the U.S. have been leading the field in terms of impact, novelty, productivity, and workforce.
  arXiv  Detail & Related papers  (2023-04-21T16:47:51Z)
• New and emerging forms of data and technologies: literature and bibliometric review [0.0]
  New and emerging forms of data present new values and opportunities for improved data driven multimedia services. Despite the special relationship between the US and the UK, there is not much evidence of collaboration in research on this topic. It is possible that the effect of the current US sanctions on China has not taken its full effect yet.
  arXiv  Detail & Related papers  (2022-10-16T09:46:22Z)
• Characterising Research Areas in the field of AI [68.8204255655161]
  We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics. The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.
  arXiv  Detail & Related papers  (2022-05-26T16:30:30Z)
• Metaethical Perspectives on 'Benchmarking' AI Ethics [81.65697003067841]
  Benchmarks are seen as the cornerstone for measuring technical progress in Artificial Intelligence (AI) research. An increasingly prominent research area in AI is ethics, which currently has no set of benchmarks nor commonly accepted way for measuring the 'ethicality' of an AI system. We argue that it makes more sense to talk about 'values' rather than 'ethics' when considering the possible actions of present and future AI systems.
  arXiv  Detail & Related papers  (2022-04-11T14:36:39Z)
• An evolutionary view on the emergence of Artificial Intelligence [0.0]
  We argue that AI emergence is associated with increasing related variety due to knowledge commonalities as well as increasing complexity. At the global level, we find increasing overall relatedness and complexity of AI. For the technological core of AI, which has been stable over time, we find decreasing related variety and increasing complexity.
  arXiv  Detail & Related papers  (2021-01-30T14:46:23Z)
• Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [98.10037444792444]
  We show how AI can empower the IoT to make it faster, smarter, greener, and safer. First, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving. Finally, we summarize some promising applications of AIoT that are likely to profoundly reshape our world.
  arXiv  Detail & Related papers  (2020-11-17T13:14:28Z)
• A Quantitative History of A.I. Research in the United States and China [0.0]
  We analyze 60 years of abstract data scraped from Scopus to explore and quantify trends in publications on A.I. topics from institutions affiliated with each country. We find the total volume of publications produced in both countries grows with a remarkable regularity over tens of years. We also see both countries undergo a seismic shift in topic choice around 1990, and connect this to an explosion of interest in neural network methods.
  arXiv  Detail & Related papers  (2020-03-05T16:55:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.