CSET's Margarita Konaev unpacks Russia's diminishing tech development as a result of tech brain drain and severed foreign partnership from its invasion of Ukraine.
CSET Research Fellow Diana Gehlhaus and a panel of distinguished experts discussed steps the United States should take to ensure a robust AI and AI-literate workforce in the future.
CSET Research Analyst Dakota Cary testified before the U.S.-China Economic and Security Review Commission hearing on "China’s Cyber Capabilities: Warfare, Espionage, and Implications for the United States." Cary discussed the cooperative relationship between Chinese universities and China’s military and intelligence services to develop talent with the capabilities to perform state-sponsored cyberespionage operations.
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.
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.
In her latest CSET report, Research Fellow Diana Gehlhaus discusses the United States' lack of a defined AI education and AI workforce policy, and offers policy recommendations.
Diana Gehlhaus, Luke Koslosky, Kayla Goode, and Claire Perkins
| October 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.
Diana Gehlhaus, Ron Hodge, Luke Koslosky, Kayla Goode, and Jonathan Rotner
| September 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.
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.
This website uses cookies.
To learn more, please review this policy. By continuing to browse the site, you agree to these terms.
This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.