Time for a Counter-AI Strategy
Abstract
The United States and China have each vowed to become the global leader in artificial intelligence (AI). In 2016, the United States published its National Artificial Intelligence Research and Development Strategic Plan. In 2017, China released its New Generation Artificial Intelligence Development Plan, announcing its intention to leapfrog the United States to become the global leader in AI by 2030 by combining government and private sector efforts.1 The United States countered with the publication of the 2018 Department of Defense Artificial Intelligence Strategy, focused on maintaining AI leadership through faster innovation and adoption, and in 2019 updated its original plan.2 The competition has been characterized as an AI arms race, measured by expenditure, number of patents filed, or speed of adoption. On the battlefield, the perceived benefits of AI are increased speed and precision as AI systems rapidly handle tasks such as target identification, freeing humans for higher-level cognitive tasks. AI will, in theory, help the military to act faster, eclipsing its adversarys ability to observe, orient, decide, and act. The singular strategic focus on gaining and maintaining leadership and the metaphor of an arms race are unhelpful, however. Races are unidimensional, and the winner takes all. Previous arms races in long-range naval artillery or nuclear weapons were predicated on the idea that advanced tech would create standoff, nullifying the effects of the adversarys weapons and deterring attack. But AI is not unidimensional; it is a diverse collection of applications, from AI-supported logistics and personnel systems to AI-enabled drones and autonomous vehicles. Nor does broadly better tech necessarily create standoff, as the US military learned from improvised explosive devices in Afghanistan. This means that in addition to improving its own capabilities, the United States must be able to respond effectively to the capabilities of others.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2020
- Accession Number
- AD1103380
Entities
People
- M. A. Thomas
Organizations
- United States Army Command and General Staff College