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. Read More
#workforceDaily Archives: October 31, 2021
Brain cell differences could be key to learning in humans and AI
Imperial researchers have found that variability between brain cells might speed up learning and improve the performance of the brain and future artificial intelligence (AI).
The new study found that by tweaking the electrical properties of individual cells in simulations of brain networks, the networks learned faster than simulations with identical cells. Read More
US Leadership in Artificial Intelligence is Still Possible
Open-source algorithms are disrupting the meaning of global artificial intelligence (AI) leadership. Here’s how the US government can use the next wave of AI to its advantage.
What does it mean to be first in developing applications of artificial intelligence (AI), and does it matter? In a recent interview, the former Chief Software Officer of the U.S. Air Force Nicolas Chaillan stated that he resigned in part because he believed that, “We have no competing chance against China in fifteen to twenty years. Right now, it’s already a done deal; it is already over.” He reasoned that a failure of the U.S. Department of Defense (DoD) to follow through on stated intentions to build up in AI and cyber means many departments within DoD still operate at what Chaillan considers a “kindergarten level.” Those are strong words, but Chaillan’s overall assessment misses the mark—the United States becoming an AI also-ran is not a foregone conclusion. Leadership in AI is not necessarily achieved by the first adopter.
There is No AI Arms Race Read More
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