Artificial intelligence offers enormous promise to advance progress, and powerful capabilities to disrupt it. This policy brief is the first installment of a series that examines how advances in AI could be exploited to enhance operations that automate disinformation. Introducing the RICHDATA framework—a disinformation kill chain—this report describes the stages and techniques used by human operators to build disinformation campaigns.

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 cset@georgetown.edu.

In science and technology, U.S. federal prize competitions are a way to promote innovation, advance knowledge, and solicit technological solutions to problems. In this report, the authors identify the unique advantages of such competitions over traditional R&D processes, and how these advantages might benefit artificial intelligence research.

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.

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.

CSET submitted this comment to the Office of Science and Technology Policy and the National Science Foundation to support the work of the National Artificial Intelligence Research Resource (NAIRR) Task Force to develop an implementation roadmap that would provide AI researchers and students across scientific disciplines access to computational resources, high-quality data, educational tools, and user support.

Software vulnerability discovery, patching, and exploitation—collectively known as the vulnerability lifecycle—is time consuming and labor intensive. Automating the process could significantly improve software security and offensive hacking. The Defense Advanced Research Projects Agency’s Cyber Grand Challenge supported teams of researchers from 2014 to 2016 that worked to create these tools. China took notice. In 2017, China hosted its first Robot Hacking Game, seeking to automate the software vulnerability lifecycle. Since then, China has hosted seven such competitions and the People’s Liberation Army has increased its role in hosting the games.

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.”