Claire Perkins, Diana Gehlhaus, Kayla Goode, Jennifer Melot, Ehrik Aldana, Grace Doerfler, and Gayani Gamage
| October 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.
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.
CSET's machine learning primer "Hacking AI" illustrates how hackers can access AI systems and argues for policymakers to build a robust and transparent AI for military systems.
According to The Hill, China is outpacing the U.S.' development of frontier technologies in part due to China's asymmetric STEM talent. According to a CSET brief, China produces twice as many STEM PhDs annually compared to the U.S.
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.
Research Analyst Emily Weinstein spoke with University World News about continued collaboration between Chinese and American university researchers amidst tensions from the China Initiative.
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.”
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