Running head ADAPTIVE LEADERSHIP .docx

Running head: ADAPTIVE LEADERSHIP
1
ADAPTIVE LEADERSHIP
4
Adaptive Leadership
Student’s Name
Institution Affiliation
Adaptive Leadership
According to Heifetz and Donald (2001), an adaptive leadership
is the kind of leadership where there is the mobilization of the
people in order to carry out the tough challenges for the purpose
of success. These challenges that needs to be mobilized are
divided into adaptive challenges and the technical fixes. Before
taking action to find the solution to this challenges, it is
important to diagnose the adaptive verses the technical
challenges. The diagnosis enables the adaptive leadership to
know the exact method that should be used to solve the
challenge successful. This is because, the adaptive challenges
requires the team or the individual to learn the new techniques
that will be used to solve the problem (Savage, n.d.). This
means that the individuals to be used in giving solutions are
required to alter their believes, loyalties and the values. But on
the other hand, the technical fixes only needs the knowledge of
the expert to solve the problem within a short period of time
(Savage, n.d).

In the career that I am pursuing, an example of the adaptive
challenge that I am wrestling with is the use of the blended
learning program to increase the knowledge and the skills of the
employees. It is among the many adaptive challenges as it
requires the employees to alter with their daily activities and
the strategies. But this can be made different by the use of the
following four competencies. With the diagnosis situation
competence, a deeper understanding of the situation together
with the different interpretations has to be done (Heifetz, &
Linsky, 2002). Understanding the blended learning program
well will enable the employment of the good techniques that
will not inconvenience the workers. This is followed by
managing self where the where the assumptions about the
strengths and the weakness are evaluated concerning the
situation. This will help in reducing the challenges by knowing
whether to maintain the program or not from the strength and
the weakness that is has. From this program, we can see that
there are a lot of the strength to reap from it hence it is of
benefit to the organization and the personal level. Next we have
intervene skillful where the program is analyzed to see if there
are chances of making progress from it (Heifetz, & Linsky,
2004). From our challenging program, we can see that it has to
be partaken because it helps in making the progress through the
gained skills and knowledge. Lastly energizing others where
they are made to be interested to attend the learning program so
that they can gain more knowledge and skills (Heifetz, &
Linsky, 2004).
References
Heifetz, A. R. & Donald L. L. (2001). "The Work of
Leadership." Harvard Business Review 79, no. 11: 131-141.
Business Source Premier, EBSCOhost.
Heifetz, R. A., & Linsky, M. (2002). "A Survival Guide for
Leaders." Harvard Business Review 80, no. 6: 65-74. Business
Source Premier, EBSCOhost.
Heifetz, R. A., & Linsky, M. (2004). "When Leadership Spells

Danger." Educational Leadership 61, no. 7: 33-37. Education
Source, EBSCOhost.
Savage, N. (n.d.). Adaptive vs. Technical - Dr. Ronald Heifetz.
Retrieved from: Adaptive vs. Technical (Links to an external
site.)
See discussions, stats, and author profiles for
this publication at:
http://www.researchgate.net/publication/273320058
The Future of Policy Informatics
CHAPTER · MARCH 2015
CITATION
1
3 AUTHORS:
Justin Longo
University of Regina
12 PUBLICATIONS 16 CITATIONS
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Dara M Wald

Iowa StateUniversity
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David M. Hondula
Arizona StateUniversity
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Available from: Justin Longo
Retrieved on: 03 September 2015
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This is a pre-print version of a chapter published as Longo, J.,
Wald, D. M., &
Hondula, D. M. (2015). The future of policy informatics. In E.
W. Johnston
(Ed.), Governance in the Information Era: Theory and Practice
of Policy Informatics (pp. 335
-352). New York: Routledge.
This version is not the final version. The revised final version

appear in the 2015
Routledge catalogue:
http://www.routledge.com/books/details/9781138832084/
Chapter 19
Justin Longo, Dara M. Wald, and David M. Hondula
The preceding pages in this volume represent the first attempt
to bring together in book form a
collection of scholars, their thoughts, and evidence, with the
objective of illustrating various
essential elements of what policy informatics is and what it
offers society. This edited collection
set out some of the themes in this emerging field, demonstrated
some of the specific
methodologies and approaches under the policy informatics
banner, and provided specific
examples set in context for appreciating the contribution policy
informatics can make in
addressing complex public policy challenges now and in the
future.
At the outset, policy informatics was defined as the study of
how computation and
communication technology is leveraged to understand and
address complex public policy and

administration problems and realize innovations in governance
processes and institutions.
Beyond the ‘how’ and ‘why’ of policy informatics, however,
lies the ‘what’, ‘where from’, and
‘where to’ of policy informatics as a field of study. In this
concluding chapter, at this point in the
early development of the field, it is useful to consider where
policy informatics comes from,
where it appears to be heading, and what the field can hope to
offer the future. We start by
considering the multidisciplinary origins of policy informatics:
how the fields of information
science, mass communication, and policy analysis—three key
foundations of policy
informatics—have each developed independently, how they
together influence the character of
policy informatics and frame future development of the field. In
transitioning between this
assessment of its past and a consideration of its future, we
pause to evaluate the place of policy
informatics in the spectrum of disciplines, interdisciplinary
fields, and research areas. We then

look to the future, noting some emerging complex policy
challenges before considering how the
field is positioned to respond in a way that takes advantage of
both its foundations and emerging
exogenous forces, specifically accelerating technology
development and momentum towards
opening governance.
The Foundations of Policy Informatics
In its most basic sense, policy informatics is an informatics
approach to the study of public
policy. Since the term ‘informatik’ was first coined by Karl
Steinbuch in 1957 to describe the
then-field of computer science, ‘informatics’ has expanded
beyond its narrow interest in the
evaluation of scientific information to include a number of
subfields including bioinformatics,
health informatics, and now policy informatics. We expand on
the informatics background
below, but those unfamiliar with the term policy informatics
need not feel embarrassed as the
field is certainly new by the standards of many fields. And
owing to its newness, the depth of the
field is relatively thin—for now.

For an indication of the relative newness of policy informatics
as a distinct field, we need
only glance at the arbiter of relevance and salience in the digital
era: Google. Whether through
the Ngram Viewer
1
that searches for the presence of particular phrases in the over
5 million
books digitized by Google (Greenfield, 2013), or in Trends
2
which measures how often a
particular search term is entered relative to all searches and thus
providing a window into what
issues appear to matter across society (Choi & Varian, 2013),
meaning, identity, and even
existence are often determined by the data amassed by the
search engine giant. Based on those
measures, policy informatics barely registers. We certainly find
the concept useful, but must
admit that the term ‘policy informatics’ can hardly be said to be
in common usage.
Policy informatics is also an understandably thin field. The
authors collected in this

volume are amongst the core of policy informatics with very
few of the field’s leaders absent
from this book. The field’s early innovators can also be found
in a small number of other
institutions such as the Virginia Bioinformatics Institute
(Advanced Computing and Informatics
Lab
3
), articulations of the policy informatics approach (e.g., Dawes
& Janssen, 2013; Helbig,
Nakashima & Dawes, 2012), and collections such as a special
issue on policy informatics in the
Public Sector Innovation Journal (Johnston & Kim, 2011), and a
forthcoming special issue on
policy informatics in the Journal of Policy Analysis and
Management.
4
The overlap amongst
these initiatives and authors confirm that the policy informatics
community is both relatively
small and cohesive, though the sustained and increasing level of
activity in this space point
towards the field’s rapid growth. Within that community, the
conceptualization of policy

informatics is also relatively cohesive. Some emphasize the data
and computational aspects of
informatics as applied to policy problems (Barrett et al., 2011),
while other point towards the
shifting notions of governance as being key to the field (e.g.,
Johnston & Hansen, 2011), but we
do not anticipate that many would object to this volume’s
definition repeated at the top of this
chapter.
We also believe that the way we have segmented the broad
disciplines and fields that
provide policy informatics with its foundations would not cause
many in the community to
register a strenuous objection. While our characterization here
is obviously influenced by our
own disciplinary perspectives, and we do not suggest that these
cover all of the traditions that
inform the policy informatics movement, the following builds
on some of the keywords in the
definition above—specifically “computation”,
“communication”, and “public policy” —to
consider three disciplinary foundations for policy informatics:

information science, mass
communications, and policy analysis approaches. While these
are by no means comprehensive
across the entire field of policy informatics, nor do they
represent the entire breadth of the
community, we argue that they address much of what is implied
under the heading policy
informatics.
The first foundational leg of the emerging field of policy
informatics might be best
described as information science, a body of scholarship which
has itself faced identity challenges
throughout its growth that persist into modern academia. The
concept of information
management (and the study of that process) has existed since
the advent of human society. While
important lessons from its past (e.g., the advent of the scroll)
offer valuable lessons for our future
(e.g., Rayward 1996), our interest is in the evolution of
information science in recent decades. In
the post World War II period, the advances in disciplines
connected to information science that
policy informatics draws on are significant: ever-expanding
computational capabilities with

respect to the speed and volume at which information can be
stored, processed, analyzed, and
visualized; the spread of mobile technologies that permit access
to information from a seemingly
infinite number of locations and situations; technological
improvements that allow for smaller
and more affordable sensors with a wide array of capabilities;
and methods by which such
information and analysis can be archived, organized, accessed,
preserved, and communicated.
These advances all provide opportunities for improving societal
capacity to address its most
pressing problems, with information science aiding the
transition of data to knowledge and
ultimately to societal wisdom (see chapter 3, in this volume).
Common terminology that we consider proximate to our
definition of information science
includes “computer science,” “data science,” “big data,”
“general systems theory,” “information
theory,” and “informatics” (e.g., Rayward 1996, Hjørland
2014). We stress that policy
informatics, with its shared roots in policy analysis and

communication, offers a more humanist
perspective than the bleak outlook painted by Anderson (2008)
for big data in which data
collection and analysis replace the theoretical foundations of
nearly all disciplines. But is it
possible to isolate information science as its own, independent
entity, from which policy
informatics may build? And where does it sit with respect to
other disciplines with a firmer
theoretical foundation?
In some aspects, information science provides no sense of
identity beyond science itself,
given Rayward’s (1996, p. 4) suggestion that “almost everything
could be argued to be
information.” Machlup and Mansfield (1983, p. 22) articulate an
only slightly refined vision,
arguing that information science is “a rather shapeless
assemblage of chunks picked from a
variety of disciplines that happen to talk about information in
one of its many meanings.” A
widely applicable definition of information science is, they
contend, impractical, based on the
different interpretations and meanings of information within
different disciplinary settings

(Machlup and Mansfield 1983). Indeed the concept of
interdisciplinary is a central tenet of many
of the other definitions for information science brought forward
in the 20th century, including the
notion of information science as an “interdiscipline” (Rayward
1996). We identify the aspects of
information science most relevant for policy informatics to be
those that are between the
subfields of computer-and-information science and library-and-
information science identified by
Machlup and Mansfield (1983), the former of which focuses on
the design and use of computers,
and the latter on the improvement of systems by which records
and documents are acquired,
stored, retrieved, and displayed (Rayward 1996). Alternatively,
Machlup and Mansfield offer a
tightly focused view that sits at the intersection of the two,
deemed “narrow” information
science, covering key elements of our vision of policy
informatics (allowing for a broad
consideration of the term ‘information system’) including novel
methods of information

exchange, control of access to information, modeling and
computer simulation of information
systems and networks, and studies of the character and behavior
of users of information systems
and services.
Connections to the other foundations of policy informatics—
mass communication and
policy analysis—are obvious, but the contributions from
information science rest in the
technological and theoretical infrastructure within which the
questions of the modern policy
informatician are addressed. Surrounding the elements
presented above, Rayward’s (1996, p. 11)
definition of information science becomes attractive: “[modern]
attempts to study in a formal and
rigorous way processes, techniques, conditions, and effects that
are entailed in improving the
efficacy of information, variously defined and understood, as
deployed and used for a range of
purposes related to individual, social and organizational needs.”
From a more utilitarian perspective, it is the roots in
information science that place the
word “informatics” in policy informatics. Definitions for
informatics date at least as far back as

the middle of the 20th century, including Mikhailov, Chernyi,
and Giljarevskij’s (1967, p. 238)
suggestion that “informatics is the discipline of science which
investigates the structure and
properties of scientific information, as well as the regularities
of scientific information activity,
its theory, history, methodology, and organization”. Hjørland
(2014) recognizes that many
sources consider informatics and information science to be
synonyms, but ultimately concludes
that the term informatics in and of itself, which has a
connotation closer to computer science than
library science, has little value except for notable exceptions:
the use of so-called ‘compound
terms’ like medical informatics, social informatics, and of
course, policy informatics.
Like its academic ‘compound term’ relatives, policy informatics
faces challenges within
academic institutions. Among these are concepts of identity and
terminology: “social informatics
studies are scattered in the journals of several different fields,
including computer science,

information systems, information science, and some social
sciences. Each of these fields uses
somewhat different nomenclature. This diversity … makes it
hard for many nonspecialists … to
locate important studies” (Kling 2007, p. 205). More
substantially, this lack of identity and the
appropriate institutional framework for emerging areas of
scholarship presents problems in the
identification of merit, as reported by Greenes and Shortliffe
(1990, p. 1119) in the field of
medical informatics: “The unique nature of the medical
informatics field was exemplified when
the thesis committee unanimously acknowledged that the work
was original and fully worthy of
a doctorate, although none felt that the scope, content, and
emphasis would have matched
precisely with the advanced degree requirements of their own
departments.” Our own experience
suggests that researchers in policy informatics could face
similar stresses in the years ahead as
most academic institutions are limited in their capacity to
rapidly adapt their framework to
appropriately recognize such ‘interdisciplines’. It is likely that
the emerging policy informatics

community at large faces analogous challenges.
Just as information science struggled to define itself as an
‘interdiscipline’, the second
foundational leg of policy informatics—communication
research—has also faced serious
questions about the range of fields, research areas, and
disciplines it can claim. The
aforementioned definition of policy informatics that frames the
discussion in this book centers on
the importance of communication in the development of
innovative governance arrangements.
An understanding of how information is processed and
communicated is a prerequisite to
fostering effective and informed decision-making. In this
respect, policy informatics also derives
much of its intellectual infrastructure from the field of
communication research. Mass
communication research as a field of inquiry also owes much to
Harold Lasswell’s work in
policy sciences (see below). After all, it was Harold Lasswell
who first described social science
as “for the intelligence needs of an age” (Peters, 1986, p. 535).
It was from this tradition that

leading interdisciplinary scholars at the University of Illinois
and University of Chicago—
including Wilbur Schramm (considered by many to be the
founder of communication studies),
the Hutchins Commission on Freedom of the Press, and Douglas
Waples (a friend and
collaborator of Lasswell’s) drew the boundaries of the field of
communications studies (Rogers
and Chaffee, 1994; Wahl-Jorgensen, 2004). During World War
II, both Schramm and Waples
worked in the Office of War Information, the domestic bureau
in charge of wartime propaganda
(Wahl-Jorgensen, 2004; Peters, 1986). Much of the early
research in the field of communication
stemmed from political concerns about persuasive
communication and the proper role of the
media in a democracy. In this respect, communication research
originated as an exemplar of the
policy sciences (Peters, 1986). Initially, the field attempted to
conform to existing disciplinary
boundaries, developing boundary organizations like the Institute
of Communications Research
5

at the University of Illinois (established by Wilbur Schramm in
1947) and the Committee on
Communication at the University of Chicago (1947-1960) to
mediate the differences between the
disciplines (Wahl-Jorgensen, 2004; Herbst, 2008). These efforts
ultimately led to the founding of
the International Communication Association in 1950 and its
flagship Journal of Communication
in 1951 (Herbst, 2008). Such organizations, journals, and
identified subfields such as political
communications (Chafee & Hochheimer, 1985) were developed
in an attempt to define the
boundaries of what was to become the field of mass
communication (Herbst, 2008).
But tension between interdisciplinary research driven by shared
interests and the
institutionalization of the field along traditional disciplinary
boundaries resulted in clashes
amongst scholars. These conflicts culminated in a public debate
published in Public Opinion
Quarterly in 1959. The debate featured Wilbur Schramm and
colleagues writing in response to
Bernard Berelson, a professor of behavioral sciences recognized

as a preeminent scholar of
public opinion and communications and one of the founders and
leaders of the Committee on
Communication at the University of Chicago (Sils, 1980). In
what has come to be described as
his “obituary of communication study,” (Wahl-Jorgensen, 2004,
p. 561) Berelson famously
asserted “as for communication research, the state is withering
away” (1959, p. 1), to which
Schramm responds that in death the communication field is in
“a somewhat livelier condition
than I had anticipated” (Schramm et al., 1959, p. 6) and
suggests that, though not without its
problems, communication research “is an extraordinarily vital
field at the moment, with a
competent and intellectually eager group of young researchers
facing a challenging set of
problems” (Schramm et al., 1959, p. 9). Despite criticism of
Schramm’s response as a “self-
celebration he constructed himself” (Wahl-Jorgensen, 2004, p.
561), his role as an advocate for a
fledgling field helped propel the field of mass communication
forward to establish it as a

legitimate discipline recognized and supported at many of the
top institutions across North
America (Wahl-Jorgensen, 2004; Herbst, 2008).
Due to the “historically permeable borders and openness of
Communication as a
discipline” (Herbst, 2008, p. 607), it developed with a
“determined eclecticism” (Menand, 2001).
Some have argued that the broad origins and disciplinary nature
of communication theory led to
a richness of ideas without a guiding domain, set of theories, or
disciplinary goals (Craig, 1999).
However, others have argued that the conscious embrace of “the
epistemological proposition of
determined eclecticism” (Herbst, p. 608)—instead of a
determined effort to ground the field
within the boxes outlined by other disciplines—contributed to
an expeditious recognition of
communication as a legitimate discipline organized around a
diverse set of methods, questions,
and theories. As a new field struggling to create a position for
itself within the academy, policy
informatics could learn much from the disciplinary struggles
fought by fields like mass

communication. Just as communication scholars battled over
how to develop a field grounded in
a unified set of theories (see Craig, 1999; Myers, 2001; Craig,
2001), the development of policy
informatics is likely to create a similar theoretical skirmish. In
this era of information and post-
disciplinarity, where “organizing structures of disciplines
themselves will not hold” (Case, 2001,
p. 150), does it make sense for policy informatics to try to
justify the boundaries of our discipline
or instead embrace the pursuit of novel questions and
disciplinary eclecticism? Before we
address this question directly, we explore the third foundational
leg of policy informatics: policy
analysis.
Turning to the part of this volume’s definition of policy
informatics focused on complex
public policy and administration problems, we see how policy
informatics owes much to the
interdisciplinary field of the policy sciences, or what has
ultimately come to be called policy
analysis.
6

Interest in increasing the relevance of the social and natural
sciences for informing
government decision making preceded World War II (Hall,
1989), but it was through the
publication of Lerner and Lasswell’s edited volume The Policy
Sciences (1951) that an
integrated, multidisciplinary approach to the study of public
problems first took shape. Harold
Lasswell drew on what he saw as the best elements of the social
sciences—principally, the
disciplines that emphasized quantitative methods in their
inquiry—and, adapting the American
pragmatism of John Dewey and others hoped for a scientific
approach to studying “the
fundamental problems of man in society, rather than upon the
topical issues of the moment”
(Lasswell, 1951, p. 8). Lasswell displays a particular respect for
the advances made in economics
and psychology during the first half of the 20th century, a
perspective that lies at the root at the
rational approach to policy analysis and the belief that human
behavior can be objectively
observed, quantitatively analyzed, and accurately predicted—a
perspective that continues to

influence the field (Morçöl, 2001).
It seems a reflection of the particular point in history that
Lasswell was writing—
immediately following the formative experiences of the Great
Depression and World War II,
immersed in a “crisis of national security” and “the urgency of
national defense” (1951, p. 3) as
motivators for a more rational and scientific approach to
governing and benefiting from the
advanced state of social science method—that led him to
highlight the policy sciences as the
great hope for the advancement of the human condition at about
the same time that Vannevar
Bush was promoting the potential contribution of computer
technology to the same end (Bush,
1945) and Wilbur Schramm was establishing the field of
communications research (see above).
Standing as a bookend to Lasswell’s seminal conceptualization
of the policy sciences in
1951 was his introductory article in the inaugural issue of the
journal Policy Sciences (Lasswell,
1970), and the subsequent expansion of those ideas in book

length (Lasswell, 1971) where he
characterized the policy approach as problem-oriented,
multidisciplinary, set within a wider
social context, and explicitly normative. Edward Quade’s
introductory editorial to the first issue
of Policy Sciences, while seeking to advance the quantitative
revolution that motivated the policy
science approach, goes to some lengths to downplay the
expectations that can be placed upon the
management and decision sciences as they are further deployed
in public policy areas. He calls
the policy sciences an effort “simply to augment, by scientific
decision methods and the
behavioral sciences, the process that humans use in making
judgments and taking decisions”
(Quade, 1970, p. 1). While the new journal sought to publish
“hard” papers that “keep the
analytical component up”, Quade stressed that the new
discipline of the policy sciences must
also recognize “extrarational and even irrational processes as
sources of knowledge” (1970, pp.
1-2).
This distinction proved to be prescient for the future of the
policy analysis movement.

Following the dominance of analytical methods throughout the
1970s (Yang, 2007), profound
shifts away from traditional analytical activities undertaken by
policy analysts, and towards
public management functions (Howlett, 2011) and the providing
of support for the political
agendas of ruling parties (Forester, 1995), began to take hold—
the very status Harold Lasswell
sought to rescue political economy from in the 1950s. As much
as policy analysis is usually
considered distinct from politics, the post-positivist policy
perspective highlights the normative
basis of policy analysis and the crucial role that politics plays
in the process (Fischer, 2003;
Mayer, van Daalen & Bots, 2004; Meltsner, 1976; Mouffe,
2000; Stone, 1997). Policy analysis
continues to struggle with the alternative views from within the
field as to how it should evolve,
between a return to its quantitative roots and a further embrace
of post-positivist efforts to
democratize policy analysis (Morçöl, 2001).
These existential struggles define the boundaries and illuminate

the various perspectives
within policy analysis, but are also useful for helping us
understand the emerging field of policy
informatics. With the world of policy analysis marked by
“ambiguity, relativism and self-doubt”
(Lawlor, 1996, p. 120), policy informatics re-engages these
debates by pursuing the contribution
that both information sciences and communications research can
make in resolving emerging
complex policy problems. To be clear, policy informatics should
not be thought of as a
technological solution to the problems of society, but rather as
the appreciation of the role that
technology can play as part of a toolset for helping society find
solutions to complex problems.
That policy informatics searches for those solutions equally in
databases, algorithms, formal
models, participatory platforms, and civic deliberation confirms
policy informatics as a direct
descendant of policy analysis.
One of the questions that often get asked of new academic
subject areas is whether it
represents an emerging discipline, a status that many wear as a
badge of honor. There is no

shortage of fields discussing whether theirs is “an emerging
academic discipline”; a sample of
the many examples would include medical informatics (Greenes
and Shortliffe, 1990),
knowledge management (Grossman, 2007), supply-chain
management (Cousins, Lawson and
Squire 2006), and nanotoxicology (Oberdörster, Oberdörster and
Oberdörster, 2005). Among the
many long-established disciplines in academia to which these
emerging fields aspire are the
standards of most university campuses such as economics,
psychology, biology, physics,
philosophy, and history. Disciplines matter so much because
academic research and university
teaching have traditionally been organized according to
disciplines, and resource allocations are
often made based on those categories (Becher and Trowler,
2001).
It is not always clear what constitutes a discipline, or
distinguishes it from a field, subject
area or sub-discipline. Take, for example, the three foundation
fields we surveyed above.

Information science continues to experience contentious
disagreement over the placement of the
term “science” (Rayward 1996), exactly what constitutes
“information”, and thus what precisely
is being studied (Hjørland 2014). Despite describing
communication as both a new discipline and
a field, Herbst (2008) suggests it still struggles to justify itself,
has failed to develop a unified
theoretical framework, and continually struggles to avoid
seclusion. And even after more than
sixty years of activity, Radin (2013, p. 6) refers to policy
analysis as “not an exact science but
rather an art.” Some criteria have been proposed for
determining when a subject becomes a
discipline: a specific topic or object of research (which may be
shared with other disciplines); a
body of accumulated specialist knowledge (usually unique to
the discipline); theories and
concepts to organize the discipline’s knowledge; a specific
technical language; specific research
methods aligned with the discipline’s research requirements;
and, crucially, an institutional
presence such as courses taught at universities, academic
departments, professional associations,

and dedicated academic journals (Krishnan, 2009, p. 9).
Based on those criteria, does policy informatics represent an
emerging discipline? The
answer, in part, lies in our field’s interest in governance
processes and outcomes over institutions
of government (Johnston, 2010). One central issue that
distinguishes policy informatics from, for
example, e-government, is its focus on governance over
government, as this volume’s definition
of policy informatics draws attention to with its reference to
innovations in governance
processes. To make explicit the distinction, a government is an
institution with formal authority
in a geo-political jurisdiction run by a combination of public
servants and political leaders who
have the power to enforce their decisions, whereas governance
describes how a range of
institutions, actors, rules, and norms, often operating across
geopolitical boundaries, come
together to influence, negotiate, and arrive at shared decisions
(Rhodes, 1996). Four features of
new governance configurations are that they operate through
partnerships rather than enforced

arrangements, are multi-jurisdictional, have a plurality of
stakeholders, and are network-based
(Bevir, 2012).
This interest in process and outcome over institutions is one
reason why the status of
discipline should not be a primary concern of policy informatics
(Kersbergen and Waarden,
2004). As new approaches to organizing academic inquiry come
to focus less on the name of the
discipline or department (a perspective that would align with a
focus on government), instead
becoming more oriented towards agile reconfigurations of
interest and inquiry, policy
informatics comes to exemplify its own focus on governance as
a way of understanding how the
field is conceptualized. The question then evolves to not
whether policy informatics is a
discipline, but rather whether that status is an appropriate goal.
In the world of Mode 2 science—
characterized by Gibbons et al. (1994) as knowledge production
that happens outside
disciplinary and academic contexts, and is problem oriented—
and in settings where innovation

in research and knowledge production is promoted (Crow, 2010;
Stehr and Weingart, 2005),
disciplines no longer have the relevance and authority they once
did. Just as governments are
challenged to explain their relevance in a world of governance
(Peters and Pierre, 1998), we
propose that policy informatics can just as usefully explore its
future as a field and contribute to
the pursuit of science without the distraction of trying to claim
for itself the status of emerging
discipline.
These foundations of the policy informatics movement
discussed above—information science,
mass communication, and policy analysis—provide a sketch of
some of the origins of the field.
In this final section, we turn to the question of where the field
might go in the future. The
development of policy informatics will draw on its disciplinary
traditions, but its future will be
forged in response to several exogenous forces including the
appreciation of complex policy

challenges, continuing advances in technology, and changing
expectations of governance. Policy
informatics is coming of age in this environment and—perhaps
more acutely with policy
informatics than other academic communities—external forces
will strongly influence the field’s
development.
Because of the uncertainty of the future and the immediacy of
the present, policy
informatics is, as much as any other field, largely a servant of
current problems. But if policy
informatics is to remain relevant, it must prove its effectiveness
in the face of emerging,
important, complex policy challenges that will confront us in
the future. Complex policy
challenges are systems level problems that exhibit features such
as profound uncertainty, rapid
emergence, multiple issue interconnectedness, and a diversity of
stakeholder interests (Geyer and
Rihani, 2010). Specific conditions of complex policy problems
include partial order (Kim, 2012),
profound uncertainty (Dryzek, 1983), and often-rapid
emergence that challenges our mental
models and predictive capacity (Howlett and Ramesh, 1995).

They are thermodynamically open
and non-linear (Homer-Dixon 2010), have whole-system
implications (Kendall 2000), and have
probabilistic rather than deterministic outcomes that are subject
to interpretation (Fischer 2003).
Owing largely to the systems dynamics strengths of policy
informatics (see especially chapters
5–8 in this volume), the field is particularly well positioned to
address complex policy
challenges.
Since we cannot know this future, we instead point towards a
brief sample of current
complex public policy challenges that can serve as examples of
the types of critical issues that
will face future policy makers and that policy informatics,
amongst other fields, will be
challenged to respond to. Climate change, more accurately
anthropogenic global warming, is one
such issue where long timescale increases in the average
temperature of the Earth’s climate
system are attributed largely to increasing concentrations of
greenhouse gases that result from

human activities (Stocker et al., 2013). The effects of increasing
global temperatures include
rising sea levels, changing precipitation patterns, and more
frequent extreme weather events
including heat waves, floods, and droughts. The climate
challenge is representative of an
emerging, important, complex policy challenge because of the
lack of current impacts that can be
attributed with certainty, the long time lags between action and
effect, the possible devastating
risks to human and natural systems, the uncertainty as to the
impact of actions taken today on
future outcomes and the uncertainty as to future impacts, the
role of natural cycles in the context
of anthropogenic forcing, and the role that future technology
may play in mitigation and
adaptation. One emerging response to the climate change
problem is global scale geoengineering
or climate engineering, which involves interventions that seek
to modify the atmosphere and
climate system at the global scale to counteract anthropogenic
global warming. Two broad types
of climate engineering efforts involve removing carbon dioxide
from the atmosphere, and

reducing the amount of sunlight reaching the earth. The
challenge of climate engineering
represents a complex policy challenge because of the untested
impact of these interventions, the
possible destructive impacts from miscalculation and
unintended consequences, the unknowns
with respect to how countries might respond to unilateral
actions by other countries, and the
absence of a global governance regime to regulation action
(Keith, Parson, and Morgan, 2010).
Examples of other issues that fall into this category of
emerging, important, complex policy
challenges include large landscape and cross-boundary resource
management, terrorism and
armed conflict (see chapter 9 in this volume), advanced robotics
and artificial intelligence,
pandemic disease (see chapter 15 in this volume), inequality
and inequity, and sexual violence.
In addition to complex policy challenges, society will continue
to witness accelerating
technology development in coming years. New developments
will be built upon previous
technologies and the pace of change will accelerate. Assuming

the continued general thrust of
Moore’s Law—that the number of transistors on an integrated
circuit doubles approximately
every two years—we can anticipate further reductions in the
cost, size, and power consumption
of computer devices. From these advances in the basics of
technology hardware, the capacity,
power, and reach of computer technology will continue to
develop. The technology outputs from
basic and applied research will, in turn, be adopted, deployed,
and reconfigured by inventors and
entrepreneurs seeking new functions and business opportunities.
Services, functions, and
applications unknown to us today will someday soon become
commonplace, while some
technologies currently occupying our focus will fail to
materialize. If we were writing this 15
years ago, following the failure of the Y2K bug to wreck havoc
as predicted (Backus et al.,
2001), we may or may not have focused on the coming
dominance of social media, the rapid
decline of traditional media and the resultant freeing up of
cognitive surplus directed towards
content production and collaboration (Shirky, 2010), the

business requirement that much Internet
content and services be offered free of charge (Anderson, 2009),
the phenomenon of “commons-
based peer production” (Benkler and Nissenbaum, 2006), the
ubiquity of powerful mobile
devices, or the accumulation of massive datasets and enthusiasm
for predictive analytics. As we
write this today, the ‘Internet of Things’—the idea that devices
in our homes, workplaces, and
public spaces, not traditionally thought of as computer devices,
will have their own IP address
and be connected to and controlled by other devices on the
Internet—is predicted to be the next
great advance in technology (Atzori, Iera, and Morabito, 2010).
This may indeed turn out to be
true. Or not. What is likely true is that some of the most
significant changes to occur in coming
years are unknown to anyone today.
However, these changes are likely to become additional tools in
the policy informatics
arsenal for addressing emerging, important, and complex policy
challenges that may confront us

in the future, while simultaneously giving rise to some of those
future policy challenges.
Whatever the future of technology development holds, policy
informatics is well situated to take
advantage of significant changes because the central premise of
the field is built upon the
application of new computation and communication
technologies. This does not mean that the
field should blindly adopt and promote every new technology.
Indeed, part of the field’s origins
in policy analysis and communication research demonstrate a
willingness to question the
negative social implications of some technology and media
developments, and the inequities that
some new technologies create and exacerbate. But to the extent
that new computation and
communication technologies can be employed to help
understand and address complex public
policy problems, policy informatics evolved to use those tools
in the service of devising
governance innovations.
While changing technology will shape society, the history of
technology use and social
development indicate that society is also capable of harnessing

technology in support of its own
preferences. We are witnessing two seemingly contradictory
though simultaneous trends with
respect to power and control: consolidation and
decentralization. The use of new technologies in
support of greater freedom, transparency, democracy, and
openness illustrate this point. From
Arab Spring revolutions in the Middle East to political
reconfigurations in America, social media
has had a profound effect on once stable governing regimes
though governments have proven
adept at using technology to reassert their authority. Once
insurmountable corporate hegemonies
have been undermined by newly available technologies,
replaced in some cases by consumer
power but also by new corporate giants. Citizen voice has been
amplified through new social
media channels, weakening the power of centralized government
institutions and strengthening
demands for wider involvement in decision-making, though the
dismissal of these diverse voices
as noise has weakened their contribution to policy making.
Transparency has become an

expectation, with the onus on public administrators to argue
why public information should not
be regularly and routinely released (McIvor, McHugh, and
Cadden, 2002), though there is
skepticism over whether transparency alone contributes to
democratic legitimacy (Lindstedt and
Naurin, 2010). The open data movement continues to promote
the regular release and availability
of government held digital data repositories for unrestricted
reuse, with at least three objectives:
to encourage third-party developed citizen services, to expand
policy networks for knowledge
creation, and to increase government transparency and
accountability (Longo, 2011). Platforms
for engaging the capacity of citizens to be active participants in
knowledge discovery,
innovation, and decision making have the potential to
strengthen our societies and our
democracies (Noveck, 2009). Participation in research and
knowledge creation can also be
facilitated by extending mechanisms such as citizen science
beyond their use to date as ways to
engage volunteer labor inputs in research activities, to including
citizen scientists in the design

and conduct of research, and the interpretation of results (Shum
et al., 2012). That these
movements have gained significant momentum in a short period
is due to the combination of
advances in technology and fuelled by the access expectations
that web users have. Policy
informatics can continue to promote this movement towards
openness not as advocates for a
normative position but by testing what works, when, and
identifying platforms that demonstrate
success.
Conclusion
The preceding has been an attempt to set the policy informatics
movement in context, to describe
some of the disciplinary traditions that inform, and what the
field can hope to offer the future.
We described a sample of the multidisciplinary origins of policy
informatics, sketching the view
from the fields of information science, mass communication,
and policy analysis. Each of these
fields continues to influence the character of policy informatics
and will continue to do so in the

future. In looking towards that future, we considered two
particular strengths of policy
informatics: its willingness and ability to adopt and shape
technology development, and its
support for the principles of opening governance.
These forces are not unequivocal benefits on the side of policy
informatics, however.
Both technology development and open governance are
essentially value-neutral forces. When
ubiquitous video technology and social networks are used to
generate a viral campaign raising
millions of dollars in donations through the “Ice Bucket
Challenge”, most would laud the power
of networked technology to raise awareness and generate
charitable giving (Townsend, 2014).
But when technology allows anyone with a 3D printer to acquire
instructions over the Internet
for constructing their own handgun, bypassing whatever
regulations may exist, we may question
the supposed benefits that knowledge sharing over the Internet
enables (Jensen-Haxel, 2011).
And as much as open governance enables policy informatics to

address complex public policy
problems and develop innovative governance solutions, it also
raises policy problems of its own
and may give rise to governance challenges. The Internet allows
citizens direct access to their
political leaders and civic debate. But when Internet trolls are
able to violate the rights of others,
acting behind a mask of anonymity to threaten violence and
promote hatred, we might ask
whether online discussion is the broken part of the Internet
(Buckels, Trapnell, and Paulhus,
2014). Advances in technology are thus neither good nor bad;
rather, they are simply inevitable.
Society will benefit greatly from having publics and scholars
that can fluently understand and
guide these future consequences from the ambiguous to the
intentional.
As we noted previously, no one knows what will happen in the
future, including us. Our
only prediction is that policy informatics will have no shortage
of public policy challenges to
address. But we will enjoy the company of a vibrant community
of scholars to investigate them
with. This book is just the start of a long conversation about

what policy informatics is and what
it can offer in the future. We are excited to be part of that
future, and to help build it together
with colleagues, governance leaders, practitioners, and citizens,
to explore ways to leverage
technology to help understand and address complex public
policy and administration problems,
and promote innovations in governance.
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analysis: theory, politics, and methods, ed. Frank, Fischer,
Gerald J. Miller, & Mara S.
Sidney, 349-368. Boca Raton, FL: CRC Press.
Endnotes
1
https://books.google.com/ngrams/graph?content=policy+informa
tics
2
http://www.google.com/trends/explore#q=policy%20informatics
3 http://www.vbi.vt.edu/about/division/Advanced-Computing-
and-Informatics-Laboratories
4 See the 2013 Call for Papers for this special issue at
http://onlinelibrary.wiley.com/store/10.1002/(ISSN)1520-
6688/asset/homepages/JPAM_Call_for_Papers_Policy_Informati
cs.pdf?v=1&s=8449bac34b958

09daf2dfeb9d2f8101e61bf307a . The special issue is scheduled
to appear in 2015, with Dr.
Anand Desai (see chapter 3 in this volume) and Dr. Yushim Kim
(School of Public Affairs,
Arizona State University) serving as co-editors.
5 http://media.illinois.edu/icr/history
6 Harold Lasswell’s preference for the term policy sciences,
grounded in his noticeable
admiration for the advancement of social science methods in the
first half of the twentieth
century, has not adhered widely in the policy literature. The
term policy analysis is the more
common term for the field that Lasswell thought of as the policy
sciences (Parsons, 1995).
20 Occupational Outlook Quarterly • Spring 2007
W
hen Will Wilkinson decided to major in phi-
losophy, his father wondered about the useful-
ness of the degree. “My dad asked if I was
going to work in a philosophy factory,” says Wilkinson.
“And now, I guess I do.”
Wilkinson is a policy analyst for a think tank in

Washington, D.C. As his anecdote suggests, think tanks
are, in a sense, idea factories. They employ policy
analysts to research complex problems and recommend
solutions. Issues range from education to healthcare to
national defense.
In fact, the ideas for many current laws and poli-
cies originated with policy analysts in think tanks and
other private organizations. Policy analysts—also called
researchers, scholars, and fellows—work to raise public
awareness of social issues, such as crime prevention,
access to healthcare, and protection of the environment.
And in the solutions they propose, these policy analysts
hope to influence government action.
Policy analysts who work for governments create
policy and evaluate program effectiveness; some help to
decide which private organizations should be awarded
publicly funded grants. For example, policy analysts
might suggest ideas for a county recycling plan, report
on how well a State project met its objectives, or propose
funds for relief organizations to aid rebuilding after a
natural disaster. Analysts in government provide deci-
sionmakers with data and hypotheses about the effects of
different policies.
Keep reading to find out more about policy analysts’
work. For the purpose of this article, policy analysts
are defined as workers who concentrate on researching,
evaluating, and shaping public policy. You’ll learn what
they do, how their research agenda is determined, what
they earn, and how they train for these careers. You’ll
also learn where to get more information about opportu-
nities in this occupation.

How they shape policy
Policy analysts work to influence political and social
decisions. Although their tasks vary, most policy analysts
work in one or more of four areas: collecting informa-
Policy analysts:
by Sadie Blanchard
Sadie Blanchard is an economist in the Office of Occupational
Statistics and Employment Projections,
BLS, (202) 691-5262.
Shaping society through research and problem-solving
Spring 2007 • Occupational Outlook Quarterly 21
tion, analyzing potential policies and making recom-
mendations, evaluating the outcomes of existing policies,
and sharing information with the public and government
officials.
Some analysts also evaluate policy philosophically.
They critique the principles behind policies and describe
the values that they believe should drive policy deci-
sions.
Collecting and compiling information. Policy
analysts gather information, especially statistical data,
to help explore issues and explain the solutions they
propose. When used correctly, statistics can identify hid-
den problems and reveal the effectiveness or ineffective-
ness of policies. Policy analysts gather new statistics by
conducting their own surveys, or they compile existing

statistics into an analysis that conveys a new meaning.
For example, one think-tank policy analyst collected
data and calculated how many low-income parents were
aware of the Earned Income Tax Credit. The calculation
allowed her to determine whether parents were benefit-
ting from this program.
Analyzing effects and recommending policies.
Policy analysts identify current or impending problems,
create solutions, and evaluate other proposed solutions.
Once a problem is recognized, researchers might attempt
to determine its causes. They may then analyze how vari-
ous policy ideas and proposals could affect the problem
and suggest solutions. After riots in Paris in 2005, for
example, the Council on Foreign Relations published
an analysis that attempted to explain the riots’ underly-
ing social causes. The council then recommended ways
in which the French Government could address these
problems.
Identifying causes and solutions is difficult, however.
Social and political problems usually have many interre-
lated causes that are hard to isolate, and the actual effects
of policies often differ from their intended results. Policy
analysts use surveys, cost-benefit analysis, focus groups,
and other tools to gauge potential policy outcomes.
Sometimes, policy analysts study the effects of new
technology. Analysts at the U.S. Federal Communica-
tions Commission, for example, study telecommunica-

tions technology and market conditions. They might
propose changes to existing regulations in response to
a new technology, or they might identify benefits and
drawbacks to a proposed change in telecommunications
rules.
Evaluating outcomes. Often, analysts try to evalu-
ate results by determining whether an existing policy has
been effective. They might begin by asking whether the
policy achieved its goal. Again, they might use statis-
tics to answer this question. They also might use focus
groups or try to identify any unintended consequences,
as when analysts at the National Bureau of Economic
Research studied whether a policy aimed at moving low-
income families to middle-class neighborhoods affected
the academic performance of children whose families
had relocated.
Policy analysts might also address a policy’s cost.
They might ask if a program has cost more than expected
and if its benefits have outweighed expenses.
The goal in these evaluations is to see how to
improve a policy—or, perhaps, whether it should be
expanded or scrapped.
Sharing information. To share their ideas and
change public policy, think-tank analysts market their
information to a wide audience that includes policymak-
ers, the media, academia, and the public. Policy ana-
lysts write books, papers, briefs, and fact sheets. Some
create electronic newsletters and send them to members
of Congress to update them on subjects discussed on
Capitol Hill. To cover some topics, analysts write issue
guides that provide facts, answers to common questions,
graphs, and links to relevant publications. Others write

editorials for newspapers and magazines. In addition,
writing for Web sites and Web logs, or blogs, is becom-
ing increasingly widespread.
Analysts also write reports and speeches. Many give
oral briefings that summarize their findings. And analysts
working for either private institutions or government
agencies are sometimes asked to testify before Congress,
advise Government officials, speak at conferences, or
appear as experts on television news programs.
Philosophizing. Some analysts debate the moral
dimensions of the law. Exploring moral questions un-
derlies many endeavors of policy analysts. For example,
policy analysts must make a value judgment to define
what is “good” before they can determine whether a
policy has led to a good outcome. Ethics are sometimes
the crux of the debate. Policy analysts whose education
or interest is in ethics or philosophy often focus on these
philosophical dimensions of policy debates.
The research agenda
The type of research that policy analysts do depends on
where they work. The mission of think tanks and asso-
ciations sets the agenda for analysts who work there. For
those working in government, research topics depend on
the needs of the government agency.
At smaller, more specialized think tanks, analysts
must be experts in their organization’s niche. Larger
think tanks may also hire policy analysts to specialize in
a particular area, but they might have generalists on staff
who research multiple areas.
Many think tanks try to avoid an ideological bias,

but others promote specific social agendas or political
philosophies. Usually, analysts who work for an organi-
zation with a particular viewpoint share that view.
Policy analysts often take the initiative when decid-
ing what to work on. They might come up with topics
on their own, or they might meet in groups to generate
proposals. Wilkinson, for example, chooses his work by
looking for gaps in research—issues that are important
but that have not been covered.
In some organizations, analysts are constrained to
topics for which they can find funding. A client or a
donor might also suggest topics.
Once a researcher has an idea, he or she writes a
policy proposal and submits it to a program leader for
approval to undertake the project. Decisions about what
to study are often driven by media and legislative inter-
est, but that doesn’t mean policy analysts pursue every
current topic. Topics must be important to an organiza-
tion or government program.
Policy analysts in government work on either broad
or specialized issues, depending on their agency and
position. These analysts must react to proposed changes
in law, regulations, and policies. They also must respond
to inquiries by government officials and the public.
Money matters
The U.S. Bureau of Labor Statistics (BLS) does not clas-
sify policy analysts as a separate occupation and, there-
fore, does not have data on their employment or earn-
ings. Depending on their research specialty, workers who
analyze policy might be counted as political scientists,

economists, sociologists, lawyers, urban and regional
planners, or natural scientists, among other titles.
Workers who analyze policy for the Federal Govern-
ment usually need significant expertise and experience.
Many are at the GS-15 level, which currently pays about
$93,000 to $145,000, depending on experience. Some
people also work as lower-level Government analysts,
helping more experienced workers or focusing on small
projects. These workers, who usually have at least a
master’s degree, often begin at the GS-7 level, which
currently pays about $31,740.
Salaries for policy analysts vary widely at think
tanks and other private organizations. Analysts’ earnings
depend on factors such as worker qualifications and the
organization’s size and budget. Earnings also depend on
how the organization gets its money. Think tanks may be
funded by endowments, individual and corporate contri-
butions, contracts with public or private organizations,
and grants from government agencies, universities, or
foundations.
At think tanks that do not have fundraising depart-
ments or large endowments, analysts are often responsi-
ble for obtaining funding. “You have to be a combination
of researcher and entrepreneur,” says think-tank analyst
Tom LaTourette. “You have to be enterprising in coming
up with new initiatives and finding funding.”
In search of funding, think-tank analysts often write
grant proposals and negotiate contracts with government

agencies and private organizations. Analysts first need
to identify the issues that will be important to specific
donors and clients, and then identify which donors and
clients might be willing to offer funds. Finally, analysts
must pitch their ideas to secure the funding.
Government analysts usually do not need to search
for funding, although they may still need to write pro-
posals about what they want to research and why.
Some policy analysts are hired as consultants by
other organizations, including Federal agencies, State
and local governments, and corporations. In such ar-
rangements, analysts are paid to evaluate the hiring
organization’s performance, identify strengths and
weaknesses, and recommend changes or to help the
organization make or analyze decisions about policy and
procedures.
Getting started and moving up
Policy analysts must be able to do independent research,
which requires reading and digesting complex informa-
tion. They communicate effectively through speaking
and writing. They must work well in groups but also be
self-starters able to work alone on a project. And they
need patience to study one subject for a long time.
In addition to these skills and traits, policy analysts
need specific types of education and experience to start
their careers.

Education. Most, but not all, policy analysts have a
graduate degree, such as a law (J.D.), doctorate (Ph.D.),
or master’s degree. The required educational background
depends on the employer, the subject being studied, and
the analyst’s work experience.
Common fields of study include economics, public
policy, and political science. But other policy analysts
have a degree in education, business administration,
philosophy, or psychology. And many analysts have a
degree related to a specific area of expertise, such as
when a healthcare analyst has a medical degree.
Analysts often choose to specialize in a field related
to their degree and then later branch into other areas.
Consider analyst—and geologist—LaTourette. He began
by using his geology education to evaluate programs in
mineworker safety. Later, he built on his experience in
safety to help establish terrorism preparedness guide-
lines.
Policy analysts who don’t have an advanced degree
can sometimes gain expertise in another way, and then
establish themselves through writing and publishing. For
example, one policy analyst at a large D.C. think tank
started as a Web administrator. He earned a good reputa-
tion as an expert in civil liberties issues by writing free-
lance articles and maintaining a popular blog. Persuaded
by his growing reputation, the think tank eventually
hired him as an analyst.
Experience. Some people begin working as policy
analysts immediately after graduate school. But because

most employers seek analysts who are already experts on
specific topics or in public policy in general, even entry-
level analysts usually have some work experience.
Would-be analysts can start getting experience while
still in school. Many college campuses have student
organizations dedicated to particular public policy
topics, and many offer open lectures and debates hosted
by the public policy or political science department.
Some analysts get experience, and expertise, by
working as college or university professors. In fact,
many senior fellows at think tanks work as university
professors at the same time, in part because much of the
work at think tanks is similar to work in academia.
Other analysts gain expertise by starting in lower-
level jobs related to policy. In some government agen-
cies, for example, entry-level program analysts assist
with policy work. Still other analysts have worked at
nonprofit organizations, such as advocacy groups.
Advisory, policy, or executive experience at a gov-
ernment agency or on a Congressional staff is another
common background for beginning analysts. Social
scientists who do statistical or other kinds of analysis can
also sometimes move into the policy arena. And working
as a journalist or freelance writer covering current events
has helped some analysts get their start.
Analysts interested in working for a policy organiza-
tion that covers a particular sector often need more spe-
cific work experience. For example, the Urban Institute’s

International Housing and Finance Team requires policy
analysts to have 5 years of legal experience in mortgage
finance, real estate, banking, or a related field.
Advancement. Like workers in most occupations,
policy analysts who succeed in their work are often
promoted. Advancement is usually based on how much
work has been published, the extent of public speaking
at conferences and public forums, the ability to attract
clients or funding, or the influence of the analyst’s work.
Some policy analysts go on to a more politically
focused career. After gaining experience, they might
work for political campaigns, for political parties, or on
Congressional staffs.
Next steps
To learn more about policy analysts, visit your local
library to find books and periodicals on subjects such as
policy analysis, public policy, and think tanks.
One of the resources available at most libraries is
the Occupational Outlook Handbook, which includes
detailed information about occupations—including
those mentioned in this article: political scientists, urban
and regional planners, economists, psychologists, other
social scientists, lawyers, and life and physical scientists.
The Handbook is also available online at
www.bls.gov/oco.
Many policy analyst jobs with the Federal Govern-
ment are posted online. You can apply for these openings
through the USAJOBS Web site, www.usajobs.gov.
Some student internships are posted on a companion site,
www.studentjobs.gov/e-scholar.asp.

You can also apply for jobs and internships by con-
tacting individual agencies or the
U.S. Office of Personnel Management
1900 E St. NW.
Washington, DC 20415
(202) 606-1800.
Possible job titles include policy analyst, program
analyst, program specialist, social scientist, policy coor-
dinator, and management and policy analyst.
The Occupational Outlook Quarterly has related ar-
ticles that you might find helpful. For tips on finding and
applying for Government jobs and internships, see “How
to get a job in the Federal Government” in the summer
2004 issue; the article is available online at
www.bls.gov/opub/ooq/2004/summer/art01.pdf. And
for more information about jobs in political and advo-
cacy groups, see “Groupmakers and grantmakers: Jobs in
advocacy, grantmaking, and civic organizations” in the
fall 2005 issue; the article is available online at
www.bls.gov/opub/ooq/2005/fall/art04.htm.
You can also find policy-related internships through
your school’s career services department and at the Web
sites of policy organizations. For an online list of, and
links to, policy organizations, see
www.c-span.org/resources/policy.asp.
To learn more about careers in policy analysis,
including where to look for internships, contact:
Association for Public Policy Analysis and Management
1029 Vermont Ave. NW., Suite 1150
Washington, DC 20005
(202) 496-0130

www.appam.org
A L e t t e r f r o m t h e e d i t o r
2 1541-1672/15/$31.00 © 2015 IEEE IEEE INTELLIGENT
SYSTEMS
Published by the IEEE Computer Society
Letters to the Editor:
Send letters, including a reference
to the article in question,
to [email protected]
Letters will be edited
for clarity and length.
Articles:
If you’re interested in submitting
an article for publication,
see our author guidelines at
www.computer.org/
intelligent/author.htm.
We’d Like to Hear from You

Editor: Daniel Zeng,
University of Arizona and
Chinese Academy of Sciences,
[email protected]
Technological advances in various computing fields, AI
included, either have already had a dramatic impact or are
perceived as potential game
changers in many applications. Take big data and social media
as cases in
point. As facilitators and the backbone of the emerging Science
2.0, they
Policy Informatics for
Smart Policy-Making
Daniel Zeng, University of Arizona and Chinese Academy of
Sciences
promise to change how the scientific enterprise operates and
innovates. In in-
dustry settings, new waves of products and services based on
these technolo-
gies, many by startups touted as tomorrow’s Google and
Facebook, are en-
tering the marketplace, improving productivity in old industry
sectors and
opening up new opportunities for future businesses yet to be
defined. In the
public sector, these technologies are starting to make similarly
profound im-
pact and promise to potentially revolutionize policy-making.
Compared with applications stemming from the scientific
community or
private sector, public-sector applications tend to take a more
conservative ap-

proach (likely rightfully so) when adapting and adopting
technology. As a
result, it’s still too early to pinpoint full-scale redesign of
policy-making ap-
proaches in major public decision-making areas, or to discuss
completed suc-
cess stories. Yet, bits and pieces of the next generation of IT-
driven policy-
making have been emerging for some time.
It’s already common knowledge that social media provides great
potential
for policy makers to gauge public opinion. Researchers and
analysts routinely
study social media content, such as Twitter feeds, to
characterize patterns of
public sentiment on various issues with policy relevance, and in
some cases, to
identify how emotion or influence propagates through online
social networks.
Understanding gained through such analyses complements the
traditional ap-
proach, which is largely based on polling, and can inform
policy-making.
In more specific public-sector application scenarios such as
emergency re-
sponse, a whole suite of information technologies, including but
not limited
to sensor networks and social media, are being integrated to
provide faster
and finer-granularity assessment of a situation. In addition,
these technolo-
gies serve as the enabling mechanism for coordination among
people as well as
resources, often in a distributed fashion, and provide timely

feedback to deci-
sion makers either during the planning phase or after the
implementation of
involved policies and decisions. In public health crisis
management, most no-
tably during the most recent Ebola epidemic, and the 2009
H1N1 (swine flu)
pandemic, social media has been heavily studied, with all kinds
of simulation-
based predictive models developed. Despite the fact that most
of these models
performed poorly (and were often outrageously wrong), the
public health com-
munity has argued for the value of such models, from the policy
standpoint.
NovEMbEr/DEcEMbEr 2015 www.computer.org/intelligent 3
Policy Informatics
Policy makers have traditionally relied
on intuition, experience, small-sample
human contact, polls, and media out-
lets to gauge society’s “pulse.” As I ar-
gued above, IT is providing innovative
alternatives to improve and comple-
ment the traditional approach. The
field of policy informatics is emerg-
ing to cross-fertilize between compu-
tational sciences and public adminis-
tration and policy, and to advance the
framework of and infrastructural sup-
port for public policy-making.
Current policy informatics research

streams emphasize traditional infor-
matics research in the context of pub-
lic policy and administration. New do-
main-specific information collection
and analysis approaches are being de-
veloped to meet the needs of complex
policy and administration problems.
Work on social media, population-
scale big open data, and temporal-
spatial-network visualization has re-
ceived a lot of attention lately; more
applied research investigates technol-
ogy adoption issues in governance
processes. Also gaining momentum is
research on new data-driven decision-
making models; complex systems view
of governance; collective intelligence;
behavioral studies of policy-makers,
policy-making processes, and the pub-
lic; and persuasive technologies.
From Informed Policy-
Making to Smart Policy-
Making
Policy informatics is in its early stage
of development, yet many of its
concepts and techniques have already
met with success in the policy re-
search community and in practice. It’s
safe to characterize the state of the art
as being largely informatics and data
science-based, focusing on better situ-
ational awareness.
In this sense, policy informatics is
already using technological means

to enable informed policy-making.
Granted, providing principled in-
formed policy-making frameworks
and tools to policy makers can have
enormous implications; concerted ef-
forts from multiple disciplines are
still needed in the years and decades
to come, to perfect such frameworks
and tools, and promote their adop-
tion. In the meantime, it makes a lot
of sense for the research community
to look beyond informed policy-mak-
ing to explore how policy informat-
ics can help build the foundation for
even better and more advanced pol-
icy-making, something more akin to
smart policy-making.
Of course, smart policy-making is
built on top of informed policy-mak-
ing, which promises effective, real-
time situational awareness and anal-
ysis capabilities to make use of data.
What advanced capabilities, then, will
differentiate smart policy-making? To
come up with a definitive set of such
differentiators won’t be possible due
to the topic’s emerging nature. But
from the current literature and on-
going discussions among academics
and practitioners, it isn’t too difficult
to venture on some novel aspects or
even pillars of next-generation smart
policy-making:

• Informed policy-making focuses
on what has happened and what
is happening. Smart policy-making
needs to take into consideration
additional information, such as
what might happen down the road.
In other words, smart policy-mak-
ing entails a much more proactive
framework.
• In informed policy-making, data
processing tends to be treated as an
independent capability, emphasiz-
ing various engineering aspects of
data sharing and mining. In smart
policy-making, the integration be-
tween data and the domain is ex-
pected to be much tighter. Various
kinds of behavioral, affect, and
root-cause analyses, at both the in-
dividual and group/population lev-
els, would need to be carried out in
particular policy contexts.
• With a significantly improved un-
derstanding of the policy environ-
ment, and much more detailed,
data-driven models, we can expect
possible major changes as to the
framing, decision-making frame-
work, and evaluation mechanism
of policy alternatives. As such, it’s
conceivable that new decision-mak-
ing tools, in addition to informat-
ics and situational awareness tools,

will play a crucial role in smart
policy-making.
Since the development of policy
informatics, AI has been a major
contributor. A significant portion of
technical work supporting informed
policy-making can be classified as
applied AI research. Smart policy-
making is expected to create more
exciting and novel research prob-
lems for AI researchers, challeng-
ing the start-of-the-art predictive
analytics, behavioral analysis, and
multi-agent simulation, among oth-
ers. In an era full of opportunities
for A I researchers in applications
such as self-driving cars, robotics,
Siri, and Cortana, it’s important for
the AI community not to forget pol-
icy-making as a fruitful area with
great potentials.
Selected CS articles and columns
are also available for free at
http://ComputingNow.computer.org.
Required Resources
Read/review the following resources for this activity:
· Textbook: Chapter 5, 6
· Lesson
· Minimum of 1 scholarly source (in addition to the textbook)
Initial Post Instructions
Rather than living in chaos, danger, and the hostility of our

neighbors, we find ways to live together. It isn't easy, but can
we avoid doing so?
If everybody has self-interest in their own welfare and safety,
then everybody also has self-interest in the welfare and safety
of others. Self-interest involves community interest, and we
must think about what we are willing to give up in order to get
that safety and stability for ourselves, our families, our
community, our nation, and even the world.
Thomas Hobbes and John Locke are just two examples of social
contract moralists. Locke's philosophy helped Thomas Jefferson
formulate the United States Declaration of Independence. We
are interested in what it means to live together in an orderly
way under a social contract.
Initial Post Instructions
For the initial post, address one of the following sets of
questions:
· What is a time when you or someone you know of experienced
a conflict between duty to self and loyalty to the community?
What would logical reasoning say should be done in that case?
Why that? What would an Ethical Egoist say to do? Why would
they say to do that? Note what you feel is the best course of
action.
· What is a time when you or someone you know experienced a
clash between professional duties and familial duties?
Reference a professional code such as that of the American
Nurses Association or American Bar Association in explaining
the clash. What moral values should have been used in that
case? Why those values? What would social contract ethics have
said to have done? Why would social contract ethics say that?
Note what you feel is the best course of action.
· Articulate and evaluate a time when you or someone you know
saw personal obligations collide with national obligations. How
did that tension involve differing positions on a moral debate?
Did those positions rely on any key moral theories? If so, how
so? If not, why not? Note what you feel is the best course of
action.

Writing Requirements
· Minimum of 2 sources cited (assigned readings/online
lessons and an outside scholarly source)
· APA format for in-text citations and list of references

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