RAND:新兴技术和风险分析:人工智能和关键基础设施(2024)

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HS AC
AN FFRDC OPERATED BY R A N D UNDER C O N T R ACT WITH DHS
HOMELAND SECURITY
OPERATIONAL ANALYSI S CENTER
RESEARCH REPORT
DANIEL M. GERSTEIN, ERIN N. LEIDY
Emerging
Technology and
Risk Analysis
Artificial Intelligence and Critical Infrastructure
T
he National Institute of Standards and
Technology’s (NIST’s) Computer Security
Resource Center defines artificial intel-
ligence (AI) as “[a] branch of computer
science devoted to developing data processing
systems that performs functions normally associ-
ated with human intelligence, such as reasoning,
learning, and self-improvement.
1
However, no
single authoritative AI taxonomy exists because
the key technologies, which come from several
fields, have each developed specific taxonomies
for AI technologies. For example, in “Adoption of
Artificial Intelligence in Smart Cities: A Compre-
hensive Review,” the authors identify six key AI
technologies used in smart cities: machine learning
(including deep learning and predictive analysis),
natural language processing (NLP) (including trans-
lation, information extraction and classification, and
clustering), computer speech (including speech to
text and text to speech), computer vision (includ-
ing image recognition and machine vision), expert
systems, and robotics.
2
This list is similar to those
developed for other applications in which AI is
being incorporated but is tailored for smart cities
and applies to AI-enabled critical infrastructure.
At a more granular level, tools supporting AI
technology development include large-language
models (LLMs), neural networks, supervised and
unsupervised training, and computational linguis-
tics. Other enabling and converging technologies
such as cyber, big data, and the Internet of Things
(IoT), have also become inextricably linked to AI
research and development (R&D). These lists and
the components that directly relate to and support
AI will likely expand as use cases continue to be
identified, AI technologies continue to evolve, and
operational AI systems are fielded.
In this report, we draw from the literature
on smart cities. As such, we consider early AI-
embedded capabilities in a city’s critical infra-
structure to be the initial stages of developing a
smart city. Inherent in this assumption is that these
infrastructure components are vital to the safe and
effective functioning of society, the safety of the
population, and the functioning of the economy. In
making this assumption, we focus on critical infra-
structure because purpose-built smart cities are
unlikely to be widespread within the time horizon of
this report (i.e., ten years). In preparing this report,
we recognize that there are many uses of AI and
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