IEEE Technology and Society Magazine - September 2021 - 84

Feature
Big Data, AI, Platforms,
and the Future of
the U.S. Intelligence
Workforce: A Research
Agenda
Kathleen M. Vogel
School for the Future of Innovation in Society,
Arizona State University, Tempe, AZ 85287-5603 USA
 Science and technology studies (STS) scholars
have long argued for a deeper appreciation of
the way technologies embody political, moral, and
social choices along with their specific technical
capabilities. In particular, research on information
technology (IT) workers has pointed out that: 1)
technology is not neutral but embodies intrinsic
characteristics that enable new human experiences
and foreclose others; 2) within these new " horizons
of the possible, " individuals and groups construct
meaning and make choices, further shaping the situation;
and 3) the interplay of intrinsic qualities and
human choices is further shaped by social, political,
and economic interests that inscribe the situation
with their intended and unintended opportunities
and limitations [1]. The U.S. intelligence workforce
includes a variety of IT-related workers. Although
attention has been devoted to discussing the social
and ethical implications of artificial intelligence (AI)
and use of big-data platforms for the public and private
sector workforces [2]-[6], few research studies
have looked at the social implications of these technologies
for the future of the defense and security
workforce [7], especially within the U.S. intelligence
Digital Object Identifier 10.1109/MTS.2021.3104384
Date of current version: 2 September 2021.
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0278-0097/21©2021 IEEE
community (IC), which constitutes a unique and varied
set of employees, actors, institutions, missions,
and policies.
For those STS scholars who have written on the
use of IT in intelligence or security matters, the
emphasis is typically on how these technologies are
creating more and varied surveillance methods for
the outside world [8]-[11] or their increased use in
security operations [12]-[14]. Although these are
important lines of inquiry, another urgent area that
few scholars have explored is the knowledge-making
process within intelligence and: 1) how big data/
AI technologies coupled with users function within
the unique, closed, and social world of intelligence;
and 2) how this tech-user relationship impacts the
knowledge created for policymakers. This lack of
scholarly attention is striking, given the size and
scope of the IC's outputs. Historian of science Galison
[15] emphasized this point:
Whether one figures by acquisition rate, by holding
size, or by contributors, the classified universe
is, as best I can estimate, on the order of five to
ten times larger than the open literature that finds
its way to our libraries. ... The closed world is not
a small strongbox in the corner of our collective
house of codified and stored knowledge. It is we in
the open world-we who study the world lodged in
IEEE Technology and Society Magazine
IEEE Technology and Society Magazine - September 2021

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