Mitchell:人机协作:重新构想的情报周期(2024)

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About the Forum
The Forum presents innovative concepts and
thought-provoking insight from aerospace
experts here in the United States and across the
globe. In order to afford publishing opportunities
for thoughtful perspectives, Mitchell Institute’s
Forum provides high visibility to writing efforts
on issues spanning technology and operational
concepts, defense policy and strategy, and
unique interpretations of changing geopolitical
relationships.
The views expressed in this paper are those of
the authors alone and do not represent the views
of the Mitchell Institute for Aerospace Studies.
Futhermore, they do not reflect the official
guidance or position of the U.S. Government, the
Department of Defense, or the Department of the
U.S. Air Force.
No. 53
January 2024
The Mitchell Forum
Human Machine Teaming:
The Intelligence Cycle Reimagined
by Lt Gen Dash Jamieson, USAF (Ret.)
Introduction
In the U.S. military, the ushering in of the digital age
introduced both a cultural shift as well as a generational divide, but
it also offered a new set of technical possibilities. Now is the time to
develop a new intelligence cycle to match the speed of information
in the 21t Century.
Technologies are developing viable capabilities much faster than
imagined just five years ago. However, the amount of information
collected by new sensor technology, as well as shared by networking
these sensors more widely, is a barrier to realizing the faster decision-
making new capabilities were intended to enable. e United States
is not alone in this predicament: our allies and partners, as well as
our adversaries, struggle with ways to overcome this barrier, but
some have begun to adapt. As the U.S. intelligence community (IC)
plays its role in assessing both opportunities and challenges related
to this problem of “too much information,” it must question some of
its most foundational elements.
Specifically, the relevance of today’s IC and the current
intelligence cycle that served as a gold standard for several decades
requires rethinking, if not reinvention. e community must
think through what artificial intelligence/machine learning (AI/
ML) paired with human machine teaming (HMT) will do to the
intelligence cycle. ere is an urgent need to identify ways to rapidly
adapt now and move forward.
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