This policy brief, authored in collaboration with the MITRE Corporation, provides a new perspective on the U.S. Department of Defense’s struggle to recruit and retain artificial intelligence talent. The authors find that the DOD already has a cadre of AI and related experts, but that this talent remains hidden. Better leveraging this talent could go a long way in meeting the DOD’s AI objectives. The authors argue that this can be done through policies that more effectively identify AI talent and assignment opportunities, processes that incentivize experimentation and changes in career paths, and investing in the necessary technological infrastructure.

The transfer of national security relevant technology—to peer competitors especially—is a well-documented problem and must be balanced with the benefits of free exchange. The following propositions covering six facets of the transfer issue reflect CSET’s current recommendations on the matter.

A new CSET reports that by 2025 China will have almost twice as many PhD STEM students as the United States.

Since the mid-2000s, China has consistently graduated more STEM PhDs than the United States, a key indicator of a country’s future competitiveness in STEM fields. This paper explores the data on STEM PhD graduation rates and projects their growth over the next five years, during which the gap between China and the United States is expected to increase significantly.

CSET's legislative roundup series highlights the latest congressional activity on science, technology and national security topics.

This issue brief explores whether artificial intelligence and AI-related certifications serve as potential pathways to enter the U.S. AI workforce. The authors find that according to U.S. AI occupation job postings data over 2010–2020, there is little demand from employers for AI and AI-related certifications. From this perspective, such certifications appear to present more hype than promise.

Artificial intelligence is said to be transforming the global economy and society in what some dub the “fourth industrial revolution.” This data brief analyzes media representations of AI and the alignments, or misalignments, with job postings that include the AI-related skills needed to make AI a practical reality. This potential distortion is important as the U.S. Congress places an increasing emphasis on AI. If government funds are shifted away from other areas of science and technology, based partly on the representations that leaders and the public are exposed to in the media, it is important to understand how those representations align with real jobs across the country.

The narrative of an artificial intelligence “arms race” among the great powers has become shorthand to describe evolving dynamics in the field. Narratives about AI matter because they reflect and shape public perceptions of the technology. In this issue brief, the second in a series examining rhetorical frames in AI, the authors compare four narrative frames that are prominent in public discourse: AI Competition, Killer Robots, Economic Gold Rush and World Without Work.

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).