Defense Primer: Emerging Technologies (CRS Report for Congress)
| Release Date |
Revised Nov. 4, 2024 |
| Report Number |
IF11105 |
| Report Type |
In Focus |
| Authors |
Kelley M. Sayler |
| Source Agency |
Congressional Research Service |
| Older Revisions |
-
Premium Revised Jan. 30, 2024 (3 pages, $24.95)
add
-
Premium Revised Nov. 14, 2022 (2 pages, $24.95)
add
-
Premium Revised Dec. 21, 2021 (3 pages, $24.95)
add
-
Premium Revised Sept. 30, 2021 (3 pages, $24.95)
add
-
Premium Revised June 8, 2021 (3 pages, $24.95)
add
-
Premium Revised Nov. 30, 2020 (122 pages, $24.95)
add
-
Premium Revised Dec. 19, 2019 (132 pages, $24.95)
add
-
Premium Revised Oct. 23, 2019 (130 pages, $24.95)
add
-
Premium Feb. 12, 2019 (3 pages, $24.95)
add
|
Summary:
Both the 2022 National Defense Strategy and senior U.S.
defense and intelligence officials have identified a number
of emerging technologies that could have a disruptive
impact on U.S. national security in the years to come. These
technologies include
• artificial intelligence,
• lethal autonomous weapon systems,
• hypersonic weapons,
• directed energy weapons,
• biotechnology, and
• quantum technology.
As these technologies continue to mature, they could hold
significant implications for congressional oversight, U.S.
defense authorizations and appropriations, military concepts
of operations, and the future of war.
Although the U.S. government has no official definition of
artificial intelligence, policymakers generally use the term
AI to refer to a computer system capable of human-level
cognition. AI is further divided into three categories:
narrow AI, general AI, and artificial superintelligence.
Narrow AI systems can perform only the specific task that
they were trained to perform, while general AI systems
would be capable of performing a broad range of tasks,
including those for which they were not specifically trained.
Artificial superintelligence refers to a system that could
exceed human-level cognition across most tasks. General
AI systems and artificial superintelligence do not yet—and
may never—exist.
Narrow AI is currently being incorporated into a number of
military applications by both the United States and its
competitors. Such applications include but are not limited
to intelligence, surveillance, and reconnaissance; logistics;
cyber operations; command and control; and semiautonomous and autonomous vehicles. These technologies
are intended in part to augment or replace human operators,
freeing them to perform more complex and cognitively
demanding work. In addition, AI-enabled systems could (1)
react significantly faster than systems that rely on operator
input, (2) cope with an exponential increase in the amount
of data available for analysis, and (3) enable new concepts
of operations, such as swarming (i.e., cooperative behavior
in which unmanned vehicles autonomously coordinate to
achieve a task) that could confer a warfighting advantage
by overwhelming adversary defensive systems.
Narrow AI could, however, introduce a number of
challenges. For example, such systems may be subject to
algorithmic bias as a result of their training data or models.
Researchers have repeatedly discovered instances of racial
bias in AI facial recognition programs due to the lack of
diversity in the images on which the systems were trained,
while some natural language processing programs have
developed gender bias. Such biases could hold significant
implications for AI applications in a military context. A
number of U.S. government documents, including DOD’s
Responsible Artificial Intelligence Strategy and
Implementation Pathway and the Framework to Advance AI
Governance and Risk Management in National Security,
provide guidance on these applications.
