Investment

National security leaders view AI as a priority technology for defending the United States. This two-part analysis is intended to help policymakers better understand the scope and implications of U.S. military investment in autonomy and AI. It focuses on the range of autonomous and AI-enabled technologies the Pentagon is developing, the military capabilities these applications promise to deliver, and the impact that such advances could have on key strategic issues.

This brief examines how the Pentagon’s investments in autonomy and AI may affect its military capabilities and strategic interests. It proposes that DOD invest in improving its understanding of trust in human-machine teams and leverage existing AI technologies to enhance military readiness and endurance. In the long term, investments in reliable, trustworthy, and resilient AI systems are critical for ensuring sustained military, technological, and strategic advantages.

The Pentagon has a wide range of research and development programs using autonomy and AI in unmanned vehicles and systems, information processing, decision support, targeting functions, and other areas. This policy brief delves into the details of DOD’s science and technology program to assess trends in funding, key areas of focus, and gaps in investment that could stymie the development and fielding of AI systems in operational settings.

Today’s research and development investments will set the course for artificial intelligence in national security in the coming years. This Executive Summary presents key findings and recommendations from CSET’s two-part analysis of U.S. military investments in autonomy and AI, including our assessment of DOD’s research priorities, trends and gaps, as well as ways to ensure U.S. military leadership in AI in the short and the long term.

CSET hosted WestExec Advisors' Michèle Flournoy and Gabrielle Chefitz, together with Avril Haines, for a discussion of their new report outlining how the Department of Defense can adapt its test, evaluation, validation and verification (TEVV) infrastructure for artificial intelligence. The authors were joined by Johns Hopkins Applied Physics Laboratory's Ashley Llorens, the Joint Artificial Intelligence Center's Dr. Jane Pinelis, and moderator Richard Danzig.

Tracking AI Investment

Zachary Arnold Ilya Rahkovsky Tina Huang
| September 2020

The global AI industry is booming, with privately held firms pulling in nearly $40 billion in disclosed investment in 2019 alone. U.S. companies continue to attract the majority of that funding—64 percent of it in 2019—but that lead is not guaranteed. This report analyzes AI investment data from 2015 to 2019 to help better understand trends in the global AI landscape.

System Re-engineering

Melissa Flagg
| September 2020

The United States must adopt a new approach to R&D policy to optimize the diversity of the current system, manage the risks of system dispersion and deliver the benefits of R&D to society. This policy brief provides a new framework for understanding the U.S. R&D ecosystem and recommendations for repositioning the role of the federal government in R&D.

CSET Founding Director Jason Matheny testified before the House Budget Committee on preparing for the potential effects of artificial intelligence on the U.S. economy. Read about VentureBeat's coverage of the hearing below.

CSET Founding Director Jason Matheny testified before the House Budget Committee for its hearing, "Machines, Artificial Intelligence, & the Workforce: Recovering and Readying Our Economy for the Future." Dr. Matheny's full testimony as prepared for delivery can be found below.

U.S. Demand for AI-Related Talent

Autumn Toney Melissa Flagg
| August 2020

The U.S. government and industry both see artificial intelligence as a pivotal technology for future growth and competitiveness. What skills will be needed to create, integrate, and deploy AI applications? This data brief analyzes market demand for AI-related jobs to determine their educational requirements, dominant sectors, and geographic distribution.