Diana Gehlhaus is a Research Fellow at the Center for Security and Emerging Technology (CSET). Prior to CSET, she was a doctoral fellow at the RAND Corporation, receiving her PhD in Policy Analysis from the Pardee RAND Graduate School. Diana’s research focuses on the intersection of tech and talent, including domestic talent pipelines in AI and other emerging technologies; workforce development and education policy; youth career and educational decision making; trends in employer hiring, recruiting, and retention; military and federal civilian talent management; and technology and telecommunications policy. Prior to RAND she was an economist and director of the Young American Prosperity Project at the Progressive Policy Institute, a policy analyst at the U.S. Export-Import Bank and an Economist for the Bureau of Labor Statistics. She has an M.A. in applied economics from Johns Hopkins University and a B.A. in mathematics and economics from Bucknell University. Diana’s media appearances include CNBC, Comcast Newsmakers, Wisconsin Public Radio, Nevada Public Radio and the Richard Fowler Show. Her research and commentary have been featured in The Hill, USA Today, Fortune, Washington Post and the Harvard Business Review blog, among other outlets.
China’s AI WorkforceNovember 2022
U.S. policies on artificial intelligence education and the AI workforce must grow, cultivate, attract, and retain the world’s best and brightest. Given China’s role as a producer of AI talent, understanding its AI workforce could provide important insight. This report provides an analysis of the AI workforce demand in China using a novel dataset of 6.8 million job postings. It then outlines potential implications along with future reports in this series.
In an opinion piece for the Council on Foreign Relations, Research Fellow Diana Gehlhaus discussed why the United States needs to make AI education a priority.
Training Tomorrow’s AI WorkforceApril 2022
Community and technical colleges offer enormous potential to grow, sustain, and diversify the U.S. artificial intelligence (AI) talent pipeline. However, these institutions are not being leveraged effectively. This report evaluates current AI-related programs and the associated number of graduates. The authors find that few AI and AI-related degrees and certificates are being awarded today. They propose five recommendations to address existing challenges and harness the potential of these institutions to train tomorrow’s AI workforce.
To Get Better at AI, Get Better at Finding AI TalentFebruary 2022
Research Fellow Diana Gehlhaus calls for coordination across the DOD to cultivating talent who can advance the use of AI in an opinion piece for Defense One.
Staying AheadNovember 2021
This research agenda provides a roadmap for the next phase of CSET’s line of research on the U.S. AI workforce. Our goal is to assist policymakers and other stakeholders in the national security community to create policies that will ensure the United States maintains its competitive advantage in AI talent. We welcome comments, feedback and input on this vision at email@example.com.
AI Education CatalogOctober 2021
Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.
In an opinion piece for The Hill, Research Fellow Diana Gehlhaus calls for a clear U.S. AI workforce policy if the U.S. wants to be the leader in AI talent drawing from her latest report.
U.S. AI Workforce: Policy RecommendationsOctober 2021
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.
The DOD’s Hidden Artificial Intelligence WorkforceSeptember 2021
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.
AI Education in China and the United StatesSeptember 2021
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.
Education in China and the United StatesSeptember 2021
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.”
China is Fast Outpacing U.S. STEM PhD GrowthAugust 2021
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.
U.S. Demand for AI CertificationsJune 2021
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.
U.S. AI WorkforceApril 2021
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.
The U.S. AI WorkforceJanuary 2021
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.