This policy brief addresses the need for a clearly defined artificial intelligence education and workforce policy by providing recommendations designed to grow, sustain, and diversify the U.S. AI workforce. The authors employ a comprehensive definition of the AI workforce—technical and nontechnical occupations—and provide data-driven policy goals. Their recommendations are designed to leverage opportunities within the U.S. education and training system while mitigating its challenges, and prioritize equity in access and opportunity to AI education and AI careers.

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.

As U.S. policymakers grapple with the need to control international technology flows, this annotated bibliography distills key lessons and surveys 50 years of scholarship, government documents, and commentary. The resources it presents are at the intersection of international economics and technology and span from the Cold War to the current challenges surrounding U.S.-China relations.

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief compares efforts to integrate AI education in China and the United States, and what advantages and disadvantages this entails. The authors consider key differences in system design and oversight, as well as strategic planning. They then explore implications for the U.S. national security community.

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief provides an overview of the education systems in China and the United States, lending context to better understand the accompanying main report, “AI Education in China and the United States: A Comparative Assessment.”

Conventional wisdom suggests that cutting-edge artificial intelligence is dependent on large volumes of data. An overemphasis on “big data” ignores the existence—and underestimates the potential—of several AI approaches that do not require massive labeled datasets. This issue brief is a primer on “small data” approaches to AI. It presents exploratory findings on the current and projected progress in scientific research across these approaches, which country leads, and the major sources of funding for this research.

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.

Summer camps are an integral part of many U.S. students’ education, but little is known about camps that focus on artificial intelligence education. This data brief maps out the AI summer camp landscape in the United States and explores the camps’ locations, target age ranges, price, and hosting organization type.

As dual-use technologies transform the national security landscape, the U.S. Department of Defense has established a variety of offices and programs dedicated to bringing private sector innovation into the military. However, these efforts have largely failed to drive cutting-edge commercial technology into major military platforms and systems. This report examines the shortcomings of the DOD’s current approach to defense innovation and offers recommendations for a more effective strategy.

For the first time, a Chinese company—Huawei—is set to lead the global transition from one key national security infrastructure technology to the next. How did Washington, at the beginning of the twenty-first century, fail to protect U.S. firms in this strategic technology and allow a geopolitical competitor to take a leadership position in a national security relevant critical infrastructure such as telecommunications? This policy brief highlights the characteristics of 5G development that China leveraged, exploited, and supported to take the lead in this key technology. The Huawei case study is in some ways the canary in the coal mine for emerging technologies and an illustration of what can happen to U.S. competitiveness when China’s companies do not have to base decisions on market forces.