China en route to becoming global leader in AI research
Tue 11 Dec 2018
China set to overtake Europe and become biggest source of AI research globally in next four years, if pace of current trend continues
A new study released by Elsevier has shined a light on the global race to lead AI research, revealing that China is outpacing its nearest competitors, the US and Europe, in the bid to become AI’s leading pioneer.
In 2004, China edged ahead of the US in terms of AI research output, but, until now, was still lagging behind Europe. But Elsevier predicts it could be top of the pack in less than 5 years if current trends continue.
China is well placed to become the world’s most productive AI powerhouse, boasting an eager government throwing substantial funds in the direction of AI industry and research, pioneering tech-firms like Tencent and Alibaba, and a virtual free-pass on citizen data – the latter crucial to accelerating the sophistication of AI applications.
To give you a flavour of its meteoric rise in the AI-stakes, last year China Money Network released a report revealing that there are now 14 Chinese AI unicorns (companies valued at $1 billion or more).
But what Elsevier’s report shows is that a crucial component to AI success is attracting and retaining the best AI talent. Over the last three years, its data shows Chinese academia is attracting more AI talent than it is losing, confirming that the country is on track to establish a leading position in AI research.
International mobility and collaboration patterns suggest that China also operates in relative isolation from the wider research community.
“China aspires to lead globally in AI and is supported by ambitious national policies,” the report reads. “A net brain gain of AI researchers in China also suggests an attractive research environment.”
AI accelerating at a pace
Wherever you stand on the political implications of China shaping and shifting the trajectory of AI’s future, the report shows AI research globally is going through a purple patch, growing by more than 12 percent annually in the past five years, compared to less than five percent for the previous five years. Research output overall, across all subject areas globally, has grown by just 0.8 percent annually over the past five years.
The US is predictably a talent magnet for European AI talent. Elsevier found US industry attracts the most AI talent from both local and international academia. In Europe, there’s a stronger move of academic talent moving to non-European industry.
Using AI to map AI
Reviewing 600,000 documents and over 700 field-specific keywords across four sectors – research, education, technology, and media – the report used semantic analysis to reveal the key focus areas of AI research.
These include: search and optimization; fuzzy systems; natural language processing and knowledge representation; computer vision; machine learning and probabilistic reasoning; planning and decision making; and neural networks.
Perhaps unsurprisingly, research in machine learning and probabilistic reasoning, neural networks, and computer vision show the largest volume of research output and growth out of the bunch.
Data used in the report comes from Elsevier’s Scopus, Fingerprint Engine, PlumX, ScienceDirect, and SciVal, RELX’s TotalPatent, and further draws on public sources, including dblp, arXiv, Stanford AI Index, kamishima.net, and Kaggle, as well as datasets provided by the Institute of Automation, Chinese Academy of Science.
Enrico Motta, professor of knowledge technologies at the Open University in the UK, and expert contributor to the report, said: “This report applies extensive text mining and semantic analytics across literature from different sectors to uncover how to more comprehensively define the AI field – essentially using AI to map AI. It is the most comprehensive characterization of AI outputs across different sectors delivered so far.”