Nowhere in the EU has the share of women in the artificial intelligence workforce been as low as in the Netherlands. We are at the bottom of the rankings in the EU with 30 per cent. Belgium did slightly worse at 33 percent. Latvia got the best score with 46 percent. The EU average is 35 percent. Europe lags behind the overall OECD average by nearly 40 percent.
This can be seen from a Study from the OECD to the supply, demand and characteristics of the ‘ai labor’ in countries affiliated with this organization for economic cooperation and development. The AI workforce includes employees with expertise in statistics, computer science, and machine learning who can actively contribute to the development and maintenance of AI systems.
Women are grossly under-represented in the EU in terms of AI, with the number of women varying widely among EU Member States. Most workers with AI skills are highly educated men. Most of them work in professions such as software developers and statisticians.
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For countries looking to get ahead of the AI race, it is important to have some insight into the size and composition of the AI workforce. Because the group formed a talent channel to attract. In 2019, less than 0.3 percent of total jobs in the EU consisted of AI talent. Therefore this group is still small, but growing rapidly. In less than a decade, their share has nearly tripled.
Northern Europe and the UK lead with 0.45%, while southern European countries such as Greece, Italy, Spain and Portugal lag behind with less than 0.27%. The Netherlands is fourth in the OECD ranking with just over 0.43% after the United Kingdom, Finland and Sweden. Belgium scores 0.36%. Between 2017 and 2019, the AI workforce grew the fastest in the Netherlands.
OECD researchers have also compiled ten AI-intensive jobs. The basis for this was formed by job advertisements in the US requiring AI skills. At the top are mathematicians, actuarial scientists, and statisticians. Then come software and application developers and analysts, followed by ICT service managers. In fourth place are database and networking professionals. Then came the electrical engineers, animal producers, life science professionals, sales/marketing/development managers, and engineering professionals.
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