China is growing in importance as a global leader in artificial intelligence (AI) research, and there is an increasing trend of researchers moving from academia to industry, especially in the United States.
A report released today shows that, globally, AI research has accelerated – growing by more than 12 per cent annually in the past five years (2013 to 2017), comparing to less than five per cent for the previous five years (2008 to 2012). By contrast, research output overall, globally across all subject areas, has grown by 0.8 percent annually over the past five years (2013 to 2017).
The analysis by Elsevier shows that industry in the United States 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.
Over the last three years, the data shows Chinese academia attracting more AI talent than it is losing, confirming that the country is on track to establish a leading position in AI research. Having overtaken the United States in AI research output in 2004, China is set to overtake Europe and become the biggest source of AI research globally in four years, if the pace of current trends continues.
Another important revelation is that despite the increasing societal reference of AI and the media attention on the ethical implications of AI, academic research on the ethics of AI has been limited.
Dan Olley, chief technology officer at Elsevier, said: 'The new generation of technologies, commonly umbrellaed as AI, are so important and yet, there appears to be no shared understanding of its exact definition. With this comprehensive study of research performance in AI we aim to provide clarity on and insights into the field’s dynamics, trends and parameters. The report is not a conclusion, but the start of a discussion on how we best enter the era of AI and increasingly symbiotic technology.'
Enrico Motta, professor of knowledge technologies at the Open University in the UK, 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 characterisation of AI outputs across different sectors delivered so far.'
Reviewing 600,000 documents and over 700 field-specific key words across four sectors – research, education, technology, and media – the semantic analysis reveals that the field of AI focusses on seven distinct research areas:
- Search and optimisation,
- Fuzzy systems,
- Natural language processing and knowledge representation,
- Computer vision,
- Machine learning and probabilistic reasoning,
- Planning and decision-making, and
- Neural networks.
Of these areas, research in machine learning and probabilistic reasoning, neural networks, and computer vision show the largest volume of research output and growth.