A lack of good data on the U.S. artificial intelligence workforce limits the potential effectiveness of policies meant to increase and cultivate this cadre of talent. In this issue brief, the authors bridge that information gap with new analysis on the state of the U.S. AI workforce, along with insight into the ongoing concern over AI talent shortages. Their findings suggest some segments of the AI workforce are more likely than others to be experiencing a supply-demand gap.
U.S. policymakers need to understand the landscape of artificial intelligence talent and investment as AI becomes increasingly important to national and economic security. This knowledge is critical as leaders develop new alliances and work to curb China’s growing influence. As an initial effort, an earlier CSET report, “AI Hubs in the United States,” examined the domestic AI ecosystem by mapping where U.S. AI talent is produced, where it is concentrated, and where AI private equity funding goes. Given the global nature of the AI ecosystem and the importance of international talent flows, this paper looks for the centers of AI talent and investment in regions and countries that are key U.S. partners: Europe and the CANZUK countries (Canada, Australia, New Zealand, and the United Kingdom).
With its massive information technology workforce, thriving research community and a growing technology ecosystem, India has a significant stake in the development of artificial intelligence globally. Drawing from a variety of original CSET datasets, the authors evaluate India’s potential for AI by examining its progress across five categories of indicators pertinent to AI development: talent, research, patents, companies and investments, and compute.
CSET partnered with the National Security Commission on Artificial Intelligence to discuss the findings and recommendations of the commissions final report, released in early March.
Luke Koslosky is a Research Analyst focusing on workforce policy, with an emphasis on increasing access to AI careers through alternative training pathways.
As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.
Many factors influence where U.S. tech multinational corporations decide to conduct their global artificial intelligence research and development (R&D). Company AI labs are spread all over the world, especially in North America, Europe and Asia. But in contrast to AI labs, most company AI staff remain concentrated in the United States. Roxanne Heston and Remco Zwetsloot explain where these companies conduct AI R&D, why they select particular locations, and how they establish their presence there. The report is accompanied by a new open-source dataset of more than 60 AI R&D labs run by these companies worldwide.
To help U.S. policymakers address long-held concerns about risks and threats associated with letting Chinese university students or graduates study in the United States, CSET experts examine which forms of collaboration, and with which Chinese universities, pose the greatest risk to U.S. research security.
As demand for cybersecurity experts in the United States has grown faster than the supply of qualified workers, some organizations have turned to artificial intelligence to bolster their overwhelmed cyber teams. Organizations may opt for distinct teams that specialize exclusively in AI or cybersecurity, but there is a benefit to having employees with overlapping experience in both domains. This data brief analyzes hiring demand for individuals with a combination of AI and cybersecurity skills.
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