IEEE Technology and Society Magazine - September 2021 - 89

and ODNI strategy documents, and other relevant
expert and practitioner interviews and reports) that
could be generated. These studies could examine:
1) narratives and framings displayed in high-level,
national AI strategy documents and pronouncements
produced by the IC; 2) local, user-identified
issues and concerns about how AI technologies will
be deployed in the intelligence workplace; and 3)
how AI strategy documents and official perspectives
compare and contrast with working-level concerns.
This would create a body of knowledge that could
better assess the varied set of sociotechnical issues
at stake in the design, development, and use of AI
technologies in the U.S. intelligence workforce at
various levels.
To reach a broad array of intelligence practitioner
audiences with this type of scholarship, one
could publish studies from this research in the
journal Intelligence and National Security and/or
the CIA's journal Studies in Intelligence and present
research findings in the Intelligence Studies section
of the International Studies Association's annual
meeting-all of which reach current and former
working-level intelligence practitioners. In addition,
the U.S. Department of State's Bureau of Intelligence
and Research's Analytic Exchange is a monthly seminar
series designed to bring academic scholars to
present research to U.S. Department of State and
intelligence practitioners. The ODNI's IC Associates
Program is another mechanism to bring academic
research insights into the IC.
thiS call for a new research agenda at the nexus
of STS and intelligence studies aims to bring new
insights into the social construction of technology,
human-centered
computing, and sociotechnical
imaginaries, as it relates to the often-closed world
of U.S. intelligence. The examination of the micro
and macro levels at which the local and national
contexts (political, economic, social, and cultural)
shape AI decision-making within intelligence will
advance insights into how high-level national intelligence
strategies and local implementation of strategies
are realized-or challenged. Such findings are
useful for academic social science scholarship to
better understand how social, political, and ethical
commitments, institutional imperatives, national
priorities, as well as technical knowledge, products,
and logics are coproduced.
September 2021
This project will provide new conceptual and
empirical resources that can be used to improve the
design and development of big-data and AI systems
in intelligence and can be used to develop improved
processes of social and ethical analysis and deliberation
on these technologies within intelligence.
Although some might be skeptical, my work illustrates
that intelligence practitioners are eager to have
these kinds of reflexive conversations about their
technical and analytic practices to improve how
they do their work. Moreover, the public and policymakers
have long been interested in the intelligence
and defense implications of IT, so we can anticipate
that their interest in the social implications of big
data and AI in security will grow. From this research
agenda, knowledge that would emerge would allow
all stakeholders who have an interest in the development
of big data and AI (technology developers,
ethicists, industry, government, public) to be better
informed as to the various values at stake, during the
early stages of technological development, while
there is still time to make important decisions about
technological choices, as well as there still being
time for intelligence and policy interventions regarding
strategies and technology implementation. This
work also is important for its ability to shed light and
increase transparency on the normally closed world
of U.S. intelligence.
New big-data and AI technologies in the intelligence
workplace can challenge traditional cultures
and work practices. Thus, involving intelligence
employees and managers in the design, implementation,
and adaptation of these kinds of technologies
will ensure that these issues are addressed to
increase acceptance of these technologies for beneficial
uses-and, in some cases, challenge existing
norms for the greater good [61], [63]. It is important
to start this analytic inquiry now, to begin to establish
some baseline empirical knowledge about big
data, AI, and its workplace implications that can be
examined and modified further as time, technologies,
and insights progress.

 References
[1] T. L. Adams, " Information technology workers, " in
Sociology of Work: An Encyclopedia, V. Smith, Ed.
Thousand Oaks, CA, USA: Sage, 2013, pp. 443-445.
[2] Y. A. Loukissas, All Data Are Local: Thinking Critically
in a Data-Driven Society. Cambridge, MA, USA: MIT
Press, 2019.
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