AI News, AI

Joint Artificial Intelligence Center Director Tells Naval War College Audience to 'Dive In' on AI

“On one side of the emerging tech equation, we need far more national security professionals who understand what this technology can do or, equally important, what it cannot do,”

“On the other side of the equation, we desperately need more people who grasp the societal implications of new technology, who are capable of looking at this new data-driven world through geopolitical, international relations, humanitarian and even philosophical lenses,”

At the Joint AI Center, established in 2018 at the Pentagon, Shanahan is responsible for accelerating the Defense Department’s adoption and integration of AI in order to quickly affect national security operations at the largest possible scale.

He told the Naval War College audience that the most valuable contribution of AI to U.S. defense will be how it helps human beings to make better, faster and more precise decisions, especially during high-consequence operations.

said the Air Force general whose prior position was director of Project Maven, a Defense Department program using machine learning to autonomously extract objects of interest from photos or video.

He compared this moment in history to the period between World War I and World War II, when new ideas led to an explosion not just in military innovation but in technology advancement that eventually helped create Silicon Valley.

Looking at the importance of military higher education in the effort, Shanahan said the role of institutions such as the Naval War College is to make a place for the military’s rising stars to think about new ways to harness AI.

The 2019 AI Index report is here!

The report aggregates a diverse set of metrics, and makes the underlying data easily accessible to the general public.  The 2019 edition tracks three times as many data sets as the 2018 edition.

Specifically, we dive into event attendance, summaries of conference topics, and policy milestones achieved.  Tracks technical progress in tasks across Computer Vision (Images, Videos, and Image+Language), Natural Language, potential limitations (Omniglot Challenge), and trends in computational capabilities.

We also examine efforts to integrate ethics into computer science curricula and look at global trends in undergraduate enrollment in introductory ML and AI courses.  Analyzes data around autonomous vehicles (AV’s) and autonomous weapons (AW’s).

We highlight countries and cities testing AV’s and present known types of autonomous weapon deployments.  Covers public perception of central banks, global governments, and the corporate world.

The Global AI Vibrancy Tool, as mentioned above, covers 28 countries across 34 metrics grouped into three high-level dimensions of AI starting in 2015: research and development, economy, and inclusion.

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