study
AI Talent Flows in Germany
Authors
Programmes
Published by
SNV
December 14, 2022
Empirical study of the career paths of AI doctoral students at German universities
Executive Summary
Discussions of the geopolitical implications of artificial intelligence (AI) often narrowly spotlight the competition between the USA and China. Assessments and comparisons of their respective strengths and weaknesses with regard to the availability of data, skilled engineers and scientists, and supercomputing infrastructure receive a lot of attention. Control over these key prerequisites determines who can best leverage AI for their own interests and geopolitical aspirations.
While the USA and China feature prominently in the discourse on the geopolitics of AI, the contributions of other regions and countries and their efforts to position themselves in the context of global cooperation and competition for the development of AI are often not part of the picture. Although the European Union (EU) is currently discussed as an important player in AI regulation, efforts to better understand the strengths and weaknesses of Europe’s AI ecosystem remain limited.
This pilot study attempts to shed light on Europe’s AI ecosystem by offering empirical insights into the mobility of AI researchers in Europe. The ability to attract and retain AI talent is a crucial indicator of the strengths and weaknesses of national AI ecosystems. It is well known that the strength of the US AI ecosystem rests on its ability to attract and retain the best global talents.
In this data brief, we analyse the pool of top AI talents for the EU’s most populated country: Germany. Our aim is to better understand how Germany is integrated into global AI talent flows. Where does Germany draw talent from? Where do young researchers go after completing their doctorates in Germany? What can the data potentially tell us about the strengths and weaknesses of the German AI ecosystem? Our analysis focuses on a self-built dataset of the career paths of PhD students supervised by the most prominent AI professors in Germany.
Our analysis offers insights into talent flows in and out of Germany. Half of the PhD students in our sample received their undergraduate degrees at foreign universities. While EU countries were found to play a much less important role as countries of origin than anticipated, China, India and Iran are more important than expected. Most PhD students remain in Germany for at least a few years after graduation. However, international doctorates, in particular, tend to leave the country after graduation. Our data show that while the USA, the UK and Switzerland hardly send any PhD students to Germany, they are important destinations for AI talent from German universities. Global tech companies that offer high salaries and research budgets are the most important employers of talents from Germany in these countries.
Our pilot study shows the potential of data-based investigations on the mobility of AI talents in Germany. We welcome further analyses of talent flows and other key factors of success in the European context. They will enable the development of measures to support Europe’s AI ecosystem in a targeted and evidence-based manner. Furthermore, such empirical insights help keep track of whether political objectives are achieved and what their actual impacts are (e.g., attracting top researchers from foreign countries or strengthening the exchange between EU member states).
Authors
Dr. Stefan Heumann
Pegah Maham
Project Director Artificial Intelligence & Data Science
Wiebke Denkena
Laurenz Hemmen
Data Scientist