Artificial Intelligence: how knowledge is created, transferred and used

Artificial Intelligence: how knowledge is created, transferred and used

The growing importance and relevance of artificial intelligence (AI) to humanity is undisputed. However, AI does not seem to have a universally agreed definition, and different sectors of society use very different vocabulary to describe AI. Using AI to define AI, we were able to detect the relevant body of research, further structure it in sub-fields, and give a comprehensive overview of the research landscape. There are strong regional differences in AI activity: • China aspires to lead globally in AI and focuses on computer vision. It shows a rapid rise in scholarly output and citation impact. A net brain gain of AI researchers to China also suggests an attractive research environment. • Europe is the largest producer of AI scholarly output, but appears to be losing academic AI talent. The broad spectrum of AI research in Europe reflects the diversity of European countries, each with their own agenda and specialties. • AI research in the United States is robust, both in terms of scholarly output and talent retention. The US benefits from a strong corporate sector. The corpus shows less diversity in AI research than Europe but more than China. A key area of further development in AI research worldwide is on ethical issues pertaining to AI. While a major topic in daily conversation, there is surprisingly little formal research published on AI ethics to date. We believe there is a need for more AI ethics research, which would bring many benefits to the field, its development, and its applications.